MBB Lab
Publications Journal publications Conference papers Book Chapters

Journal publications

  1. Gang Qu, Anton Orlichenko, Junqi Wang, Gemeng Zhang, Li Xiao, Kun Zhang, Tony W Wilson, Julia M Stephen, Vince D Calhoun, Yu-Ping Wang, Interpretable Cognitive Ability Prediction: A Comprehensive Gated Graph Transformer Framework for Analyzing Functional Brain Networks, IEEE Transactions on Medical Imaging, Date of Publication: Dec 18 2023; PMID: 38109241; DOI: 10.1109/TMI.2023.3343365
  2. Wei Wang, Li Xiao, Gang Qu, Vince D. Calhoun, Yu-Ping Wang, Multiview hyperedge-aware hypergraph embedding learning for multisite, multiatlas fMRI based functional connectivity network analysis, Medical Image Analysis, Date of Publication: May 2024; DOI: https://doi.org/10.1016/j.media.2024.103144
  3. Irina Belyaeva, Ben Gabrielson, Yu-Ping Wang,Tony W Wilson, Vince D Calhoun, Julia M Stephen, Tulay Adali, Learning Spatiotemporal Brain Dynamics in Adolescents via Multimodal MEG and fMRI Data Fusion Using Joint Tensor/Matrix Decomposition, IEEE Transactions on Biomedical Engineering, Date of Publication: Feb 12 2024; DOI: 10.1109/TBME.2024.3364704
  4. Abraham D Killanin, Thomas W Ward, Christine M Embury, Vince D Calhoun, Yu-Ping Wang, Julia M Stephen, Giorgia Picci, Elizabeth Heinrichs-Graham, Tony W Wilson, Better with age: Developmental changes in oscillatory activity during verbal working memory encoding and maintenance, Developmental Cognitive Neuroscience, Date of Publication: Feb 3 2024; DOI: 10.1016/j.dcn.2024.101354
  5. Mikki Schantell, Brittany K Taylor, Amirsalar Mansouri, Yasra Arif, Anna T Coutant, Danielle L Rice, Yu-Ping Wang, Vince D Calhoun, Julia M Stephen, Tony W Wilson, Theta oscillatory dynamics serving cognitive control index psychosocial distress in youth, Neurobiology of Stress, Date of Publication: Dec 2023; DOI: 10.1016/j.ynstr.2023.100599
  6. Lindong Jiang, Chao Xu, Yuntong Bai, Anqi Liu, Yun Gong, Yu-Ping Wang, Xiaoyan Sun, Autosurv: interpretable deep learning framework for cancer survival analysis incorporating clinical and multi-omics data, npj Precision Oncology, Date of Publication: Jan 05 2024; DOI: https://doi.org/10.1038/s41698-023-00494-6
  7. Giorgia Picci, Chloe C Casagrande, Lauren R Ott, Nathan M Petro, Nicholas J Christopher-Hayes, Hallie J Johnson, Madelyn P Willett, Hannah J Okelberry, Yu-Ping Wang,Julia M Stephen, Vince D Calhoun, Tony W Wilson, Dehydroepiandrosterone mediates associations between trauma-related symptoms and anterior pituitary volume in children and adolescents, Human Brain Mapping, Date of Publication: Oct 18 2023; DOI: 10.1002/hbm.26516
  8. Giorgia Picci, Lauren R Ott, Samantha H Penhale, Brittany K Taylor, Hallie J Johnson, Madelyn P Willett, Hannah J Okelberry, Yu-Ping Wang, Vince D Calhoun, Julia M Stephen, Tony W Wilson, Developmental changes in endogenous testosterone have sexually-dimorphic effects on spontaneous cortical dynamics, Human Brain Mapping, Date of Publication: Dec 1 2023; DOI: 10.1002/hbm.26496
  9. Anton Orlichenko, Grant Daly, Ziyu Zhou, Anqi Liu, Hui Shen, Hong-Wen Deng, Yu-Ping Wang, ImageNomer: Description of a functional connectivity and omics analysis tool and case study identifying a race confound, Neuroimage: Reports, Date of Publication: Nov 7 2023; DOI: https://doi.org/10.1016/j.ynirp.2023.100191
  10. Chen Qiao, Bin Gao, Yuechen Liu, Xinyu Hu, Wenxing Hu, Vince D. Calhoun, Yu-Ping Wang, Deep learning with explainability for characterizing age-related intrinsic differences in dynamic brain functional connectivity, Medical Image Analysis, Date of Publication: Sep 1 2023; DOI: https://doi.org/10.1016/j.media.2023.102941
  11. Chao-Ying Zhang, Qiu-Hua Lin, Yan-Wei Niu, Wei-Xing Li, Xiao-Feng Gong, Fengyu Cong, Yu-Ping Wang, Vince D Calhoun, Denoising brain networks using a fixed mathematical phase change in independent component analysis of magnitude-only fMRI data, Human Brain Mapping, Date of Publication: Aug 30 2023; DOI: 10.1002/hbm.26471
  12. Giorgia Picci, Nathan M Petro, Jake J Son, Oktay Agcaoglu, Jacob A Eastman, Yu-Ping Wang, Julia M Stephen, Vince D Calhoun, Brittany K Taylor, Tony W Wilson, Transdiagnostic indicators predict developmental changes in cognitive control resting-state networks, Development and Psychopathology, Date of Publication: Aug 24 2023; DOI: 10.1017/S0954579423001013
  13. Giorgia Picci, Lauren R Ott, Nathan M Petro, Chloe C Casagrande, Abraham D Killanin, Danielle L Rice, Anna T Coutant, Yasra Arif, Christine M Embury, Hannah J Okelberry, Hallie J Johnson, Seth D Springer, Haley R Pulliam, Yu-Ping Wang, Vince D Calhoun, Julia M Stephen, Elizabeth Heinrichs-Graham, Brittany K Taylor, Tony W Wilson, Developmental alterations in the neural oscillatory dynamics underlying attentional reorienting, Developmental Cognitive Neuroscience, Date of Publication: Aug 6 2023; DOI: 10.1016/j.dcn.2023.101288
  14. Dawn Jensen, Jiayu Chen, Jessica A Turner, Julia M Stephen, Yu-Ping Wang, Tony W Wilson, Vince D Calhoun, Jingyu Liu, Epigenetic associations with adolescent grey matter maturation and cognitive development, Frontiers in Genetics, Date of Publication: July 17 2023; doi: 10.3389/fgene.2023.1222619
  15. Nathan M Petro, Giorgia Picci, Christine M Embury, Lauren R Ott, Samantha H Penhale, Maggie P Rempe, Hallie J Johnson, Madelyn P Willett, Yu-Ping Wang, Julia M Stephen, Vince D Calhoun, Gaelle E Doucet, Tony W Wilson, Developmental differences in functional organization of multispectral networks, Cerebral Cortex, Date of Publication: July 05 2023; DOI: 10.1093/cercor/bhad193
  16. Abraham D Killanin, Brittany K Taylor, Christine M Embury, Giorgia Picci, Yu-Ping Wang, Vince D Calhoun, Julia M Stephen, Elizabeth Heinrichs-Graham, Tony W Wilson, Testosterone levels mediate the dynamics of motor oscillatory coding and behavior in developing youth, Developmental Cognitive Neuroscience, Date of Publication: Jun 1 2023; DOI: 10.1016/j.dcn.2023.101257
  17. Lan Yang, Chen Qiao, Huiyu Zhou, Vince D. Calhoun, Julia M. Stephen, Tony W. Wilson, Yu-Ping Wang, Explainable Multimodal Deep Dictionary Learning to Capture Developmental Differences from Three fMRI Paradigms, IEEE Transactions on Biomedical Engineering, Date of Publication: Feb 14 2023; DOI: 10.1109/TBME.2023.3244921
  18. Jake J. Son, Mikki Schantell, Giorgia Picci, Yu-Ping Wang, Julia M. Stephen, Vince D. Calhoun, Gaelle E. Doucet, Brittany K. Taylor, Tony W. Wilson, Altered longitudinal trajectory of default mode network connectivity in healthy youth with subclinical depressive and posttraumatic stress symptoms, Developmental Cognitive Neuroscience, Date of Publication: Feb 27 2023; DOI: https://doi.org/10.1016/j.dcn.2023.101216
  19. Anton Orlichenko, Gang Qu, Gemeng Zhang, Binish Patel, Tony W. Wilson, Julia M. Stephen, Vince D Calhoun, Yu-Ping Wang, Latent Similarity Identifies Important Functional Connections for Phenotype Prediction, IEEE Transactions on Biomedical Engineering, Date of Publication: Dec 29 2022; DOI: 10.1109/TBME.2022.3232964
  20. Faming Xu, Chen Qiao, Huiyu Zhou, Vince D.Calhoun, Julia M.Stephen, Tony W.Wilson, Yu-Ping Wang, An explainable autoencoder with multi-paradigm fMRI fusion for identifying differences in dynamic functional connectivity during brain development, Neural Networks, Date of Publication: Feb 2023; DOI: https://doi.org/10.1016/j.neunet.2022.12.007
  21. Maggie P Rempe, Lauren R Ott, Giorgia Picci, Samantha H Penhale, Nicholas J Christopher-Hayes, Brandon J Lew, Nathan M Petro, Christine M Embury, Mikki Schantell, Hallie J Johnson, Hannah J Okelberry, Kathryn L Losh, Madelyn P Willett, Rebecca A Losh, Yu-Ping Wang, Vince D Calhoun, Julia M Stephen, Elizabeth Heinrichs-Graham, Max J Kurz, Tony W Wilson, Spontaneous cortical dynamics from the first years to the golden years, Proceedings of the National Academy of Sciences of the United States of America, Date of Publication: Jan 18 2023; DOI: 10.1073/pnas.2212776120
  22. Anees Abrol, Zening Fu, Yuhui Du, Tony W Wilson, Yu-Ping Wang, Julia M Stephen, Vince D Calhoun, Developmental and aging resting functional magnetic resonance imaging brain state adaptations in adolescents and adults: A large N (>47K) study, Human Brain Mapping, Date of Publication: Jan 11 2023; DOI: 10.1002/hbm.26200
  23. Madison H Fung, Elizabeth Heinrichs-Graham, Brittany K Taylor, Michaela R Frenzel, Jacob A Eastman, Yu-Ping Wang, Vince D Calhoun, Julia M Stephen, Tony W Wilson, The development of sensorimotor cortical oscillations is mediated by pubertal testosterone, NeuroImage, Date of Publication: Nov 09 2022; DOI: 10.1016/j.neuroimage.2022.119745
  24. Gemeng Zhang, Biao Cai, Aiying Zhang, Zhuozhuo Tu, Li Xiao, Julia M Stephen, Tony W Wilson, Vince D Calhoun, Yu-Ping Wang, Detecting abnormal connectivity in schizophrenia via a joint directed acyclic graph estimation model, NeuroImage, Date of Publication: Jul 13 2022; DOI: 10.1016/j.neuroimage.2022.119451
  25. Amy S. Badura Brack, Marika Marklin, Christine M. Embury, Giorgia Picci, Michaela R.Frenzel, Alicia Klanecky Earl, Julia M Stephen, Yu-Ping Wang, Vince D Calhoun, Tony W Wilson, Neurostructural brain imaging study of trait dissociation in healthy children, BJPsych Open, Date of Publication: Sep 23 2022; DOI: 10.1192/bjo.2022.576
  26. Samantha H.Penhale, Giorgia Picci, Lauren R.Ott, Brittany K.Taylor, Michaela R.Frenzel, Jacob A.Eastman, Yu-Ping Wang, Vince D Calhoun, Julia M Stephen, Tony W Wilson, Impacts of adrenarcheal DHEA levels on spontaneous cortical activity during development, Developmental Cognitive Neuroscience, Date of Publication: Sep 16 2022; DOI: https://doi.org/10.1016/j.dcn.2022.101153
  27. Irina Belyaeva, Ben Gabrielson, Yu-Ping Wang,Tony W. Wilson, Vince D. Calhoun, Julia M. Stephen & Tulay Adali Multi-Subject Analysis for Brain Developmental Patterns Discovery via Tensor Decomposition of MEG Data, Neuroinformatics, Date of Publication: Aug 24 2022; DOI: https://doi.org/10.1007/s12021-022-09599-y
  28. Chen Zhao, Haipeng Tang, Daniel McGonigle, Zhuo He, Chaoyang Zhang, Yu-Ping Wang, Hong-Wen Deng, Robert Bober, Weihua Zhou, Development of an approach to extracting coronary arteries and detecting stenosis in invasive coronary angiograms, Journal of Medical Imaging, Date of Publication: July 19 2022; doi: https://doi.org/10.1117/1.JMI.9.4.044002
  29. Liangliang Liu, Yu-Ping Wang, Yi Wang, Pei Zhang, Shufeng Xiong, An enhanced multi-modal brain graph network for classifying neuropsychiatric disorders, Medical Image Analysis, Date of Publication: July 16 2022; DOI: https://doi.org/10.1016/j.media.2022.102550
  30. Nathan M Petro, Lauren R Ott, Samantha H Penhale, Maggie P Rempe, Christine M Embury, Giorgia Picci, Yu-Ping Wang, Julia M Stephen, Vince D Calhoun, Tony W Wilson, Eyes-closed versus eyes-open differences in spontaneous neural dynamics during development, NeuroImage, Date of Publication: May 27 2022; DOI: 10.1016/j.neuroimage.2022.119337
  31. Madison H Fung, Raeef L Rahman, Brittany K Taylor, Michaela R Frenzel, Jacob A Eastman, Yu-Ping Wang, Vince D. Calhoun, Julia M. Stephen, Tony W. Wilson, The impact of pubertal DHEA on the development of visuospatial oscillatory dynamics, Human Brain Mapping, Date of Publication: July 01 2022; DOI: 10.1002/hbm.25991
  32. Xueli Song, Rongpeng Li, Kaiming Wang, Yuntong Bai, Yuzhu Xiao, Yu-Ping Wang, Joint Sparse Collaborative Regression on Imaging Genetics Study of Schizophrenia, IEEE/ACM Transactions on Computational Biology and Bioinformatics, Date of Publication: 3 May 2022; DOI: 10.1109/TCBB.2022.3172289
  33. Giorgia Picci, Brittany K. Taylor, Abraham D. Killanin, Jacob A. Eastman, Michaela R. Frenzel, Yu-Ping Wang, Julia M. Stephen, Vince D. Calhoun, Tony W. Wilson, Left amygdala structure mediates longitudinal associations between exposure to threat and long-term psychiatric symptomatology in youth, Human Brain Mapping, Date of Publication: May 18 2022; DOI:https://doi.org/10.1002/hbm.25904
  34. Giorgia Picci, Nicholas J.Christopher-Hayes, Nathan M.Petro, Brittany K.Taylor, Jacob A.Eastman, Michaela R.Frenzel, Yu-Ping Wang, Julia M. Stephen, Vince D. Calhoun, Tony W. Wilson, Amygdala and hippocampal subregions mediate outcomes following trauma during typical development: Evidence from high-resolution structural MRI, Neurobiology of Stress, Date of Publication: May 2022; DOI:https://doi.org/10.1016/j.ynstr.2022.100456
  35. Liangliang Liu, Jing Chang, Ying Wang, Gongbo Liang, Yu-Ping Wang, Hui Zhang, Decomposition-Based Correlation Learning for Multi-modal MRI Based Classification of neuropsychiatric disorders, Frontiers in in Neuroscience, Date of Publication: April 21 2022; doi: https://doi.org/10.3389/fnins.2022.832276
  36. Yipu Zhang, Haowei Zhang, Li Xiao, Yuntong Bai, Vince D. Calhoun, Yu-Ping Wang, Multi-modal imaging genetics data fusion via a hypergraph-based manifold regularization: application to schizophrenia study, IEEE Transactions on Medical Imaging, Page(s):1-1, Date of Publication: Mar 23 2022; DOI: 10.1109/TMI.2022.3161828
  37. Hailin Yue, Jin Liu, Junjian Li, Hulin Kuang, Jinyi Lang, Jianhong Cheng, Lin Peng, Yongtao Han, Harrison Bai, Yu-Ping Wang, Qifeng Wang, Jianxin Wang, MLDRL: Multi-loss disentangled representation learning for predicting esophageal cancer response to neoadjuvant chemoradiotherapy using longitudinal CT images, Medical Image Analysis, Volume 79, Date of Publication: July 2022; DOI: https://doi.org/10.1016/j.media.2022.102423
  38. Li Xiao, Biao Cai, Gang Qu, Gemeng Zhang, Julia M. Stephen, Tony W. Wilson, Vince D Calhoun, Yu-Ping Wang, Distance Correlation-Based Brain Functional Connectivity Estimation and Non-Convex Multi-Task Learning for Developmental fMRI Studies, IEEE Transactions on Biomedical Engineering, Date of Publication: Mar 22 2022; DOI: 10.1109/TBME.2022.3160447
  39. Brittany K.Taylor, ElizabethHeinrichs-Graham, Jacob A.Eastman, Michaela R.Frenzel, Yu-Ping Wang, Vince D.Calhoun, Julia M.Stephen, Tony W.Wilson, Longitudinal changes in the neural oscillatory dynamics underlying abstract reasoning in children and adolescents, NeuroImage, Date of Publication: Mar 10 2022; DOI: 10.1016/j.neuroimage.2022.119094
  40. Weizheng Yan, Gang Qu, Wenxing Hu, Anees Abrol, Biao Cai, Chen Qiao, Sergey M. Plis, Yu-Ping Wang, Jing Sui, Vince D. Calhoun, Deep Learning in Neuroimaging: Promises and challenges, IEEE Signal Processing Magazine, Date of Publication: Feb 24 2022; DOI: 10.1109/MSP.2021.3128348
  41. Yuchen Pei, Guocheng Shi, Wenjin Xia, Chen Wen, Dazhen Sun, Fang Zhu, Jiang Li, Zhongqun Zhu, Xiaoqing Liu, Meiping Huang, Yu-Ping Wang, Huiwen Chen, Lisheng Wang, Building A Risk Prediction Model for Postoperative Pulmonary Vein Obstruction via Quantitative Analysis of CTA Images, IEEE Journal of Biomedical and Health Informatics, Date of Publication: Jan 27 2022; DOI: 10.1109/JBHI.2022.3146590
  42. Brittany K Taylor, Michaela R Frenzel, Jacob A Eastman, Christine M Embury, Oktay Agcaoglu, Yu-Ping Wang, Julia M Stephen, Vince D Calhoun, Tony W Wilson, Individual differences in amygdala volumes predict changes in functional connectivity between subcortical and cognitive control networks throughout adolescence, Neuroimage, Date of Publication: Feb 15 2022; DOI: 10.1016/j.neuroimage.2021.118852
  43. Abraham D Killanin, Christine M Embury, Giorgia Picci, Elizabeth Heinrichs-Graham, Yu-Ping Wang, Vince D Calhoun, Julia M Stephen, Tony W Wilson, Trauma moderates the development of the oscillatory dynamics serving working memory in a sex-specific manner, Cerebral Cortex, Date of Publication: Feb 01 2022; DOI: 10.1093/cercor/bhac008
  44. Oktay Agcaoglu, Tony W Wilson, Yu-Ping Wang,Julia M Stephen, Zening Fu, Vince D Calhoun, Altered Resting fMRI Spectral Power in Data-Driven Brain Networks During Development: A Longitudinal Study, Journal of Neuroscience Methods, Date of Publication: Feb 22 2022; DOI: 10.1016/j.jneumeth.2022.109537
  45. Biao Cai, Zhongxing Zhou, Aiying Zhang, Gemeng Zhang, Li Xiao, Julia M Stephen, Tony W Wilson, Vince D Calhoun, Yu-Ping Wang, Functional connectomes incorporating phase synchronization for the characterization and prediction of individual differences, Journal of Neuroscience Methods, Date of Publication: Feb 24 2022; DOI: 10.1016/j.jneumeth.2022.109539
  46. Felicha T Candelaria-Cook, Isabel Solis 1, Megan E Schendel, Yu-Ping Wang, Tony W Wilson, Vince D Calhoun, Julia M Stephen, Developmental trajectory of MEG resting-state oscillatory activity in children and adolescents: a longitudinal reliability study, Cerebral Cortex, Date of Publication: Feb 28 2022; DOI: 10.1093/cercor/bhac023
  47. Gang Qu, Wenxing Hu, Li Xiao, Junqi Wang, Yuntong Bai, Beenish Patel, Kun Zhang, Yu-Ping Wang, Brain Functional Connectivity Analysis via Graphical Deep Learning, IEEE Transactions on Biomedical Engineering, Date of Publication: Dec 9 2021; DOI: 10.1109/TBME.2021.3127173
  48. Gang Qu, Li Xiao, Wenxing Hu, Junqi Wang, Kun Zhang, Vince D Calhoun, Yu-Ping Wang, Ensemble manifold regularized multi-modal graph convolutional network for cognitive ability prediction, IEEE Transactions on Biomedical Engineering, Date of Publication: May 11 2021; DOI: 10.1109/TBME.2021.3077875
  49. Wenxing Hu, Xianghe Meng, Yuntong Bai, Aiying Zhang, Gang Qu, Biao Cai, Gemeng Zhang, Tony W. Wilson, Julia M. Stephen, Vince D. Calhoun, Yu-Ping Wang, Interpretable multimodal fusion networks reveal mechanisms of brain cognition, IEEE Transactions on Medical Imaging, Page(s):1-1, Date of Publication: February 08 2021; DOI: 10.1109/TMI.2021.3057635
  50. Yue Han, Qiu-Hua Lin, Li-Dan Kuang, Xiao-Feng Gong, Fengyu Cong, Yu-Ping Wang, Vince D Calhoun, Low-Rank Tucker-2 Model for Multi-Subject fMRI Data Decomposition with Spatial Sparsity Constraint, IEEE Transactions on Medical Imaging, Date of Publication: Oct 22 2021; DOI: 10.1109/TMI.2021.3122226
  51. Alexej Gossmann, Aria Pezeshk, Yu-Ping Wang, Berkman Sahiner Test Data Reuse for the Evaluation of Continuously Evolving Classification Algorithms Using the Area under the Receiver Operating Characteristic Curve, SIAM Journal on Mathematics of Data Science, Date of Publication: June 03 2021; DOI: https://doi.org/10.1137/20M1333110
  52. Isabel Solis, Jacki Janowich, Felicha Candelaria-Cook, William Collishaw, Yu-Ping Wang, Tony W Wilson, Vince D Calhoun, Kristina R T Ciesielski, Julia M Stephen, Frontoparietal network and neuropsychological measures in typically developing children, Neuropsychologia, Date of Publication: Aug 20 2021;DOI: 10.1016/j.neuropsychologia.2021.107914
  53. Lauren R Ott, Samantha H Penhale, Brittany K Taylor, Brandon J Lew, Yu-Ping Wang, Vince D Calhoun, Julia M Stephen, Tony W Wilson, Spontaneous cortical MEG activity undergoes unique age- and sex-related changes during the transition to adolescence, Neuroimage, Date of Publication: Dec 1 2021; DOI: 10.1016/j.neuroimage.2021.118552
  54. Yun Gong, Junxiao Yang, Xiaohua Li, Cui Zhou, Yu Chen, Zun Wang, Xiang Qiu, Ying Liu, Huixi Zhang, Jonathan Greenbaum, Liang Cheng, Yihe Hu, Jie Xie, Xuecheng Yang, Yusheng Li, Yuntong Bai, Yu-Ping Wang, Yiping Chen, Li-Jun Tan, Hui Shen, Hong-Mei Xiao, Hong-Wen Deng, A systematic dissection of human primary osteoblasts in vivo at single-cell resolution, Aging(Albany NY), Date of Publication: Aug 24 2021;DOI: 10.18632/aging.203452
  55. Md Ashad Alam, Chuan Qiu, Hui Shen, Yu-Ping Wang,Hong-Wen Deng, A generalized kernel machine approach to identify higher-order composite effects in multi-view datasets, with application to adolescent brain development and osteoporosis, Journal of Biomedical Informatics, Date of Publication: July 6 2021; DOI: 10.1016/j.jbi.2021.103854
  56. Madison H Fung, Brittany K Taylor, Brandon J Lew, Michaela R Frenzel, Jacob A Eastman, Yu-Ping Wang, Vince D Calhoun, Julia M Stephen, Tony W Wilson , Sexually dimorphic development in the cortical oscillatory dynamics serving early visual processing, Developmental Cognitive Neuroscience, Date of Publication: May 26 2021;DOI: 10.1016/j.dcn.2021.100968
  57. Chen Qiao, Xin-Yu Hu, Li Xiao, Vince D. Calhoun, Yu-Ping Wang, A deep autoencoder with sparse and graph Laplacian regularization for characterizing dynamic functional connectivity during brain development, Neurocomputing, Date of Publication: May 6 2021; DOI: https://doi.org/10.1016/j.neucom.2021.05.003
  58. David E Warren, Anthony J Rangel, Nicholas J Christopher-Hayes, Jacob A Eastman, Michaela R Frenzel, Julia M Stephen, Vince D. Calhoun, Yu-Ping Wang, Tony W Wilson, Resting-state functional connectivity of the human hippocampus in periadolescent children: Associations with age and memory performance, Human Brain Mapping, Date of Publication: May 12 2021; DOI:10.1002/hbm.25458; PMID: 33978276
  59. Brittany K Taylor, Jacob A Eastman, Michaela R Frenzel, Christine M Embury, Yu-Ping Wang, Vince D.Calhoun, Julia M.Stephen, Tony W.Wilson, Neural oscillations underlying selective attention follow sexually divergent developmental trajectories during adolescence, Developmental Cognitive Neuroscience, Date of Publication: May 7 2021; DOI: 10.1016/j.dcn.2021.100961; PMID: 33984667
  60. Thomas DeRamus, Ashkan Faghiri, Armin Iraji, Oktay Agcaoglu, Victor Vergara, Zening Fu, Rogers Silva, Harshvardhan Gazula, Julia Stephen, Tony W Wilson, Yu-Ping Wang, Vince D.Calhoun, Modular and state-relevant functional network connectivity in high-frequency eyes open vs eyes closed resting fMRI data, Journal of Neuroscience Methods, Date of Publication: May 2 2021; DOI: 10.1016/j.jneumeth.2021.109202; PMID: 33951454
  61. Junqi Wang, Li Xiao, Wenxing Hu, Gang Qu , Tony W. Wilson, Julia M. Stephen, Vince D. Calhoun, Yu-Ping Wang, Functional network estimation using multigraph learning with application to brain maturation study, Human Brain Mapping, Date of Publication: 31 March 2021; DOI: https://doi.org/10.1002/hbm.25410
  62. Biao Cai, Gemeng Zhang, Aiying Zhang, Li Xiao, Wenxing Hu, Julia M. Stephen, Tony W. Wilson, Vince D. Calhoun, Yu-Ping Wang, Functional connectome fingerprinting: Identifying individuals and predicting cognitive functions via autoencoder, Human Brain Mapping, Date of Publication: 09 April 2021; DOI: https://doi.org/10.1002/hbm.25394
  63. Biao Cai, Gemeng Zhang, Aiying Zhang, Wenxing Hu, Julia M.Stephen, Tony W.Wilson, Vince D.Calhoun, Yu-Ping Wang, A GICA-TVGL framework to study sex differences in resting state fMRI dynamic connectivity, Journal of Neuroscience Methods, Volume 332, Date of Publication: 15 February 2020; DOI: https://doi.org/10.1016/j.jneumeth.2019.108531
  64. Chuan Qiu, Fangtang Yu, Kuanjui Su, Qi Zhao, Lan Zhang, Chao Xu, Wenxing Hu, Zun Wang, Lanjuan Zhao, Qing Tian, Yu-Ping Wang, Hongwen Deng, Hui Shen, Multi-omics Data Integration for Identifying Osteoporosis Biomarkers and Their Biological Interaction and Causal Mechanisms, iScience, Volume 23, Issue 2, Date of Publication: 21 February 2020; DOI: https://doi.org/10.1016/j.isci.2020.100847
  65. Mackenzie S Mills, Christine M Embury, Alicia K Klanecky, Maya M Khanna, Vince D Calhoun, Julia M Stephen, Yu-Ping Wang, Tony W Wilson, Amy S Badura-Brack, Traumatic Events Are Associated with Diverse Psychological Symptoms in Typically-Developing Children, Journal of Child & Adolescent Trauma, Date of Publication: 19 Aug 2020; DOI: 10.1007/s40653-019-00284-y
  66. Liangliang Liu, Shaojie Tang, Fangxiang Wu, Yu-Ping Wang, Jianxin Wang, An ensemble hybrid feature selection method for neuropsychiatric disorder classification, IEEE/ACM Transactions on Computational Biology and Bioinformatics, Date of Publication: 20 Jan 2021; DOI: 10.1109/TCBB.2021.3053181
  67. Guixia Pan, Li Xiao, Yuntong Bai, Tony W Wilson, Julia M Stephen, Vince D Calhoun, Yu-Ping Wang, Multiview Diffusion Map Improves Prediction of Fluid Intelligence with Two Paradigms of fMRI Analysis, IEEE Transactions on Biomedical Engineering, Date of Publication: Dec 31 2020; DOI: 10.1109/TBME.2020.3048594
  68. Chen Qiao, Lan Yang, Vince D.Calhoun, Zong-Ben Xu, Yu-Ping Wang, Sparse deep dictionary learning identifies differences of time-varying functional connectivity in brain neuro-developmental study, Neural Networks, Date of Publication: Dec 07 2020; DOI: https://doi.org/10.1016/j.neunet.2020.12.007
  69. Brittany K.Taylor, Jacob A.Eastman, Michaela R.Frenzel, Christine M.Embury,Yu-Ping Wang, Julia M.Stephen, Vince D.Calhoun, Amy S.Badura-Brack, Tony W.Wilson, Subclinical Anxiety and Posttraumatic Stress Influence Cortical Thinning During Adolescence, Journal of the American Academy of Child & Adolescent Psychiatry, Date of Publication: Nov 22 2020; DOI: https://doi.org/10.1016/j.jaac.2020.11.020
  70. Yuntong Bai, Yun Gong, Jianchao Bai, Jingyu Liu, Hong-Wen Deng, Vince D. Calhoun, Yu-Ping Wang, A joint analysis of multi-paradigm fMRI data with its application to cognitive study, IEEE Transactions on Medical Imaging, Page(s):1-1, Date of Publication: 07 December 2020 ; DOI: 10.1109/TMI.2020.3042786
  71. JM Stephen, I Solis, J Janowich, M Stern, MR Frenzel, JA Eastman, MS Mills, CM Embury, NM Coolidge, E Heinrichs-Graham, A Mayer, J Liu, YP Wang, TW Wilson, VD Calhoun The Developmental Chronnecto-Genomics (Dev-CoG) Study: A Multimodal Study on the Developing Brain, NeuroImage, Accepted 5 October 2020, Available online 8 October 2020; DOI: https://doi.org/10.1016/j.neuroimage.2020.117438
  72. Brittany K Taylor, Michaela R Frenzel, Jacob A Eastman, Alex I Wiesman, Yu-Ping Wang, Vince D Calhoun, Julia M Stephen, Tony W Wilson Reliability of the NIH toolbox cognitive battery in children and adolescents: a 3-year longitudinal examination, Psychological Medicine, Oct 9 2020; DOI: 10.1017/S0033291720003487
  73. Dathan C Gleichmann, Isabel Solis, Jacqueline R Janowich, Yu-Ping Wang, Vince D Calhoun, Tony W Wilson, Julia M Stephen Troubled Hearts: Association Between Heart Rate Variability and Depressive Symptoms in Healthy Children, Applied Psychophysiology and Biofeedback,Sep 25 2020; DOI: 10.1007/s10484-020-09488-7
  74. Li Xiao, Xiang-Gen Xia, Yu-Ping Wang, Exact and Robust Reconstructions of Integer Vectors Based on Multidimensional Chinese Remainder Theorem (MD-CRT), IEEE Transactions on Signal Processing, Date of Publication: Sep 15 2020; DOI: 10.1109/TSP.2020.3023584
  75. Oktay Agcaoglu, Tony W Wilson, Yu-Ping Wang, Julia Stephen, Vince Calhoun, Dynamic Resting State Connectivity Differences in Eyes Open versus Eyes Closed Conditions, Brain Connectivity, Date of Publication: Sep 7 2020; DOI:10.1089/brain.2020.0768
  76. Li Xiao, Aiying Zhang, Biao Cai, Julia M Stephen, Tony W Wilson, Vince D Calhoun, Yu-Ping Wang, Correlation Guided Graph Learning to Estimate Functional Connectivity Patterns from fMRI Data, IEEE Transactions on Biomedical Engineering, Date of Publication: Sep 7 2020; DOI: 10.1109/TBME.2020.3022335
  77. Yi-Pu Zhang, Li Xiao, Gemeng Zhang, Biao Cai, Julia M Stephen, Tony W Wilson, Vince D Calhoun, Yu-Ping Wang, Multi-paradigm fMRI fusion via sparse tensor decomposition in brain functional connectivity study, IEEE Journal of Biomedical and Health Informatics, Date of Publication: Aug 25 2020; DOI: 10.1109/JBHI.2020.3019421
  78. Liangliang Liu, FangXiang Wu, Yu-Ping Wang, Jianxin Wang, Multi-Receptive-Field CNN for Semantic Segmentation of Medical Images, IEEE Journal of Biomedical and Health Informatics, Date of Publication: Aug 13 2020; DOI: 10.1109/JBHI.2020.3016306
  79. Elizabeth Heinrichs-Graham, Brittany K Taylor, Yu-Ping Wang, Julia M Stephen, Vince D Calhoun, Tony W Wilson, Parietal Oscillatory Dynamics Mediate Developmental Improvement in Motor Performance, Cerebral Cortex, Date of Publication: Jul 24 2020; DOI: 10.1093/cercor/bhaa199
  80. Zhongxing Zhou, Biao Cai, Gemeng Zhang, Aiying Zhang, Vince D. Calhoun, Yu-Ping Wang, Prediction and classification of sleep quality based on phase synchronization related whole-brain dynamic connectivity using resting state fMRI, NeuroImage, Accepted 19 July 2020, Available online 22 July 2020; DOI: https://doi.org/10.1016/j.neuroimage.2020.117190
  81. Abraham D.Killanin, Alex I. Wiesman, Elizabeth Heinrichs-Graham, Boman Groff, Michaela R. Frenzel, Jacob A. Eastman, Yu-Ping Wang, Vince D. Calhoun, Julia M. Stephen, Tony W. Wilson Development and Sex Modulate Visuospatial Oscillatory Dynamics in Typically-Developing Children and Adolescents, NeuroImage, Accepted 20 July 2020, Available online 22 July 2020; DOI: https://doi.org/10.1016/j.neuroimage.2020.117192
  82. Madison H Fung, Brittany K Taylor, Michaela R Frenzel, Jacob A Eastman, Yu-Ping Wang, Vince D Calhoun, Julia M Stephen, Tony W Wilson, Pubertal Testosterone Tracks the Developmental Trajectory of Neural Oscillatory Activity Serving Visuospatial Processing, Cerebral Cortex, Original Article; 2020; 00: 1-12, Date of Publication: 24 June 2020; DOI: https://doi.org/10.1093/cercor/bhaa169
  83. Peyman Hosseinzadeh Kassani, Li Xiao, Gemeng Zhang, Julia M. Stephen, Tony W. Wilson, Vince D. Calhoun, Yu-Ping Wang, Causality based Feature Fusion for Brain Neuro-Developmental Analysis, IEEE Transactions on Medical Imaging, Page(s):1-1, Date of Publication: 24 April 2020; DOI: 10.1109/TMI.2020.2990371
  84. Peng Peng, Yipu Zhang, Yongfeng Ju, Kaiming Wang, Gang Li, Vince D. Calhoun, Yu-Ping Wang, Group Sparse Joint Non-negative Matrix Factorization on Orthogonal Subspace for Multi-modal Imaging Genetics Data Analysis, IEEE/ACM Transactions on Computational Biology and Bioinformatics, Page(s):1-1, Date of Publication: 02 June 2020; DOI: 10.1109/TCBB.2020.2999397
  85. Chen Qiao, Yan Shi, Yu-Xian Diao, Vince D. Calhoun, Yu-Ping Wang, Log-sum enhanced sparse deep neural network, Neurocomputing, Volume 407, 24 September 2020, Pages 206-220; DOI: https://doi.org/10.1016/j.neucom.2020.04.118
  86. Amy S. Badura-Brack, Mackenzie S. Mills, Christine M. Embury, Maya M. Khanna, Alicia Klanecky Earl, Julia M. Stephen, Yu-Ping Wang, Vince D. Calhoun, Tony W. Wilson, Hippocampal and parahippocampal volumes vary by sex and traumatic life events in children, J Psychiatry Neurosci, Published online on Feb. 20, 2020; DOI: 10.1503/jpn.190013
  87. Liangliang liu, Jianhong Cheng, Quan Quan, Fang-Xiang Wu, Yu-Ping Wang, Jianxin Wang, A Survey on U-shaped networks in Medical Image Segmentations, Neurocomputing, Published online on 1 June 2020; DOI: https://doi.org/10.1016/j.neucom.2020.05.070
  88. Yipu Zhang, Peng Peng, Yongfeng Ju, Gang Li, Vince D. Calhoun, Yu-Ping Wang, Canonical Correlation Analysis of Imaging Genetics Data Based on Statistical Independence and Structural Sparsity, IEEE Journal of Biomedical and Health Informatics, Page(s):1-1, Date of Publication: 10 February 2020; DOI: 10.1109/JBHI.2020.2972581
  89. Junqi Wang, Li Xiao, Tony W.Wilson, Julia M.Stephen, Vince D. Calhoun, Yu-Ping Wang, Examining Brain Maturation during Adolescence Using Graph Laplacian Learning Based Fourier Transform, Journal of Neuroscience Methods, Available online 10 March 2020, 108649, In Press; DOI: https://doi.org/10.1016/j.jneumeth.2020.108649
  90. Brittany K.Taylor, Christine M.Embury, ElizabethHeinrichs-Graham, Michaela R.Frenzel, Jacob A.Eastman, Alex I.Wiesman, Yu-Ping Wang, Vince D.Calhoun, Julia M.Stephen, Tony W.Wilson, Neural oscillatory dynamics serving abstract reasoning reveal robust sex differences in typically-developing children and adolescents, Developmental Cognitive Neuroscience, Volume 42, April 2020, 100770; DOI: https://doi.org/10.1016/j.dcn.2020.100770
  91. Keith Dillon, Yu-Ping Wang, Resolution-based spectral clustering for brain parcellation using functional MRI, Journal of Neuroscience Methods, Received 19 March 2019, Revised 3 January 2020, Accepted 3 February 2020, Available online 5 February 2020; Volume 335, 1 April 2020, 108628; DOI: https://doi.org/10.1016/j.jneumeth.2020.108628
  92. Yuntong Bai, Zille Pascal, Vince D. Calhoun, Yu-Ping Wang, Optimized Combination of Multiple Graphs with Application to the Integration of Brain Imaging and (epi)Genomics Data, IEEE Transactions on Medical Imaging, Date of Publication: 06 December 2019; DOI: 10.1109/TMI.2019.2958256
  93. Li Xiao, Junqi Wang, Peyman H. Kassani, Yipu Zhang, Yuntong Bai, Julia M. Stephen, Tony W. Wilson, Vince D. Calhoun, Yu-Ping Wang, Multi-Hypergraph Learning Based Brain Functional Connectivity Analysis in fMRI Data, IEEE Transactions on Medical Imaging, Date of Publication: 02 December 2019; DOI: 10.1109/TMI.2019.2957097
  94. Faghiri A, Stephen J, Wang YP, W Wilson T, Calhoun VD, Brain development includes linear and multiple nonlinear trajectories: a cross-sectional resting-state fMRI study, Brain Connectivity, 2019 Nov 19. PMID: 31744324; DOI: 10.1089/brain.2018.0641
  95. Li G, Han D, Wang C, Hu W, Calhoun VD, Wang YP, Application of deep canonically correlated sparse autoencoder for the classification of schizophrenia, Comput Methods Programs Biomed, 2020 Jan; 183:105073. PMID: 31525548; DOI: 10.1016/j.cmpb.2019.105073; Epub 2019 Sep 9.
  96. Aiying Zhang, Jian Fang, Wenxing Hu, Vince D. Calhoun, Yu-Ping Wang, A Latent Gaussian Copula Model for Mixed Data Analysis in Brain Imaging Genetics, IEEE/ACM Transactions on Computational Biology and Bioinformatics, Date of Publication: 01 November 2019; DOI: 10.1109/TCBB.2019.2950904
  97. Gemeng Zhang, Biao Cai, Aiying Zhang, Julia M. Stephen, Tony W. Wilson, Vince D. Calhoun, Yu-Ping Wang, Estimating Dynamic Functional Brain Connectivity with a Sparse Hidden Markov Model, IEEE Transactions on Medical Imaging, Date of Publication: 19 July 2019; DOI: 10.1109/TMI.2019.2929959
  98. Yuntong Bai, Pascal Zille, Wenxing Hu, Vince D. Calhoun, Yu-Ping Wang, Biomarker Identification Through Integrating fMRI and Epigenetics, IEEE Transactions on Biomedical Engineering, Date of Publication: 02 August 2019; DOI: 10.1109/TBME.2019.2932895
  99. Biao Cai, Gemeng Zhang, Wenxing Hu, Aiying Zhang, Pascal Zille, Yipu Zhang, Julia M. Stephen, Tony W. Wilson, Vince D. Calhoun, Yu-Ping Wang, Refined measure of functional connectomes for improved identifiability and prediction, Human Brain Mapping, Date of Publication: 29 July 2019; PMID: 31355994; DOI: 10.1002/hbm.24741
  100. Li-Dan Kuang, Qiu-Hua Lin, Xiao-Feng Gong, Fengyu Cong, Yu-Ping Wang, Vince D. Calhoun, Shift-Invariant Canonical Polyadic Decomposition of Complex-Valued Multi-Subject fMRI Data with a Phase Sparsity Constraint, IEEE Transactions on Medical Imaging, Date of Publication: 19 August 2019; PMID: 31355994; DOI: 10.1109/TMI.2019.2936046
  101. Hao He, Shaolong Cao, Ji-gang Zhang, Hui Shen, Yu-Ping Wang, Hong-wen Deng, A Statistical Test for Differential Network Analysis Based on Inference of Gaussian Graphical Model, Scientific Reports, Date of Publication: 2019 Jul 26;9(1):10863; PMID: 31350445; PMCID: PMC6659630; DOI: 10.1038/s41598-019-47362-7
  102. Md. Ashad Alam, Osamu Komori, Hong-Wen Deng, Vince D. Calhoun, Yu-Ping Wang, Robust Kernel Canonical Correlation Analysis to Detect Gene-Gene Co-associations: A Case Study in Genetics, Journal of Bioinformatics and Computational Biology, Date of Publication: 10 May 2019; DOI: https://doi.org/10.1142/S0219720019500288
  103. Li Xiao, Julia M. Stephen, Tony W. Wilson, Vince D. Calhoun, Yu-Ping Wang, A Manifold Regularized Multi-Task Learning Model for IQ Prediction from Two fMRI Paradigms, IEEE Transactions on Biomedical Engineering, Date of Publication: 05 June 2019; DOI: 10.1109/TBME.2019.2921207
  104. Li Xiao, Julia M. Stephen, Tony W. Wilson, Vince D. Calhoun, Yu-Ping Wang, Alternating Diffusion Map Based Fusion of Multimodal Brain Connectivity Networks for IQ Prediction, IEEE Transactions on Biomedical Engineering, Date of Publication: 29 November 2018; DOI: 10.1109/TBME.2018.2884129
  105. Aiying Zhang, Biao Cai, Wenxing Hu, Bochao Jia, Faming Liang, Tony W. Wilson, Julia M. Stephen, Vince D. Calhoun, Yu-Ping Wang, Joint Bayesian-incorporating estimation of multiple Gaussian graphical models to study brain connectivity development in adolescence, IEEE Transactions on Medical Imaging, Date of Publication: 03 July 2019; DOI: 10.1109/TMI.2019.2926667
  106. Peyman Hosseinzadeh Kassani, Alexej Gossmann, Yu-Ping Wang, Multimodal Sparse Classifier for Adolescent Brain Age Prediction, IEEE Journal of Biomedical and Health Informatics, Date of Publication: 28 June 2019; DOI: 10.1109/JBHI.2019.2925710
  107. Wenxing Hu, Biao Cai, Aiying Zhang, Vince D. Calhoun, Yu-Ping Wang, Deep collaborative learning with application to multimodal brain development study, IEEE Transactions on Biomedical Engineering, Date of Publication: 13 March 2019; DOI: 10.1109/TBME.2019.2904301
  108. Wenxing Hu, Aiying Zhang, Biao Cai, Vince D. Calhoun, Yu-Ping Wang, Distance canonical correlation analysis with application to an imaging-genetic study, J. of Medical Imaging, 6(2), 026501 (2019). DOI: https://doi.org/10.1117/1.JMI.6.2.026501
  109. Junbo Duan, Han Liu, Lanling Zhao, Xiguo Yuan, Yu-Ping Wang, and Mingxi Wan, Detection of False-Positive Deletions from the Database of Genomic Variants, BioMed Research International, Volume 2019, Article ID 8420547, 8 pages; DOI: https://doi.org/10.1155/2019/8420547
  110. Yue Qiu, Qiu-Hua Lin, Li-Dan Kuang, Xiao-Feng Gong, Fengyu Cong, Yu-Ping Wang, Vince D. Calhoun, Spatial source phase: A new feature for identifying spatial differences based on complex-valued resting-state fMRI data, Human Brain Mapping banner, First published: 27 February 2019; DOI: https://doi.org/10.1002/hbm.24551
  111. Xiang X, Wang YP, Cao H, Zhang X, Knowledge database assisted gene marker selection for chronic lymphocytic leukemia, J Int Med Res., 2018 Aug;46(8):3358-3364. DOI: 10.1177/0300060518783072. Epub 2018 Jul 12. PMID: 29996709
  112. Zheng Y, Wang YP, Cao H, Chen Q, Zhang X, Integrated computational biology analysis to evaluate target genes for chronic myelogenous leukemia, Mol Med Rep., 2018 Aug;18(2):1766-1772. DOI: 10.3892/mmr.2018.9125. Epub 2018 Jun 5., PMID: 29901125
  113. Min Wang, Ting-Zhu Huang, Jian Fang, Vince D. Calhoun, Yu-Ping Wang, Integration of imaging (epi)genomics data for the study of schizophrenia using group sparse joint nonnegative matrix factorization, IEEE/ACM Transactions on Computational Biology and Bioinformatics, Date of Publication: 14 February 2019; DOI: 10.1109/TCBB.2019.2899568
  114. Biao Cai, Gemeng Zhang, Aiying Zhang, Julia M. Stephen, Tony W. Wilson, Vince D. Calhoun, Yu Ping Wang, Capturing Dynamic Connectivity from Resting State fMRI using Time-Varying Graphical Lasso, IEEE Trans. on Biomedical Engineering, DOI: 10.1109/TBME.2018.2880428
  115. Aiying Zhang, Jian Fang, Faming Liang, Vince D. Calhoun, and Y.P. Wang, Aberrant Brain Connectivity in Schizophrenia Detected via a Fast Gaussian Graphical Model, Date of Publication: 09 July 2018, IEEE Journal of Biomedical and Health Informatics, DOI: 10.1109/JBHI.2018.2854659, PMID: 29994624
  116. Alexej Gossmann, Pascal Zille, V. D. Calhoun and Y.P. Wang, FDR-Corrected Sparse Canonical Correlation Analysis with Applications to Imaging Genomics, Date of Publication: 13 March 2018, IEEE Trans. Medical Imaging, 2018 Aug; 37(8):1761-1774. DOI: 10.1109/TMI.2018.2815583, PMID: 29993802
  117. Oktay Agcaoglu, Tony Wilson, Yu-Ping Wang, Julia Stephen, Vince D. Calhoun, Resting state connectivity differences in eyes open versus eyes closed conditions, First published: 05 February 2019, Human Brain Mapping. DOI: https://doi.org/10.1002/hbm.24539
  118. Junbo Duan, Jerome Idier, Yu-Ping Wang, Mingxi Wan, A joint least squares and least absolute deviation model, Date of Publication: 06 February 2019, IEEE Signal Processing Letters. DOI: 10.1109/LSP.2019.2897863, PMID: 29993802
  119. Junbo Duan, Charles Soussen, David Brie, Jérôme Idier, Yu-Ping Wang, Mingxi Wan, A parallelizable framework for segmenting piecewise signals, IEEE Access, 28 December 2018; Page(s): 1 - 1, Electronic ISSN: 2169-3536, DOI: 10.1109/ACCESS.2018.2890077
  120. Trevarrow MP, Kurz MJ, McDermott TJ, Wiesman AI, Mills MS, Wang YP, Calhoun VD, Stephen JM, Wilson TW, The developmental trajectory of sensorimotor cortical oscillations, NeuroImage, 2019 Jan 1; 184:455-461. DOI: 10.1016/j.neuroimage.2018.09.018. Epub 2018 Sep 12. PMID:30217545
  121. Christine M. Embury, Alex I. Wiesman, Amy L. Proskovec, Mackenzie S. Mills, Elizabeth Heinrichs-Graham, Yu-Ping Wang, Vince D. Calhoun, Julia M. Stephen, Tony W. Wilson, Neural dynamics of verbal working memory processing in children and adolescents, NeuroImage, 2018 Oct 16; 185:191-197. DOI: https://doi.org/10.1016/j.neuroimage.2018.10.038 PMID: 30336254
  122. E. Heinrichs-Graham, T. McDermott, M. Mills, A. Wiesman, Y.P. Wang, Julia M. Stephen, V. Calhoun, T. Wilson, The lifespan trajectory of neural oscillatory activity in the motor system, Developmental Cognitive Neuroscience, 2018 Apr; 30:159-168, doi: 10.1016/j.dcn.2018.02.013, PMID: 29525417, PMCID: PMC5949086
  123. Jian Fang, Chao Xu, Pascal Zille, Dongdong Lin, Hong-Wen Deng, Vince D. Calhoun, and Yu-Ping Wang, Fast and Accurate Detection of Complex Imaging Genetics Associations Based on Greedy Projected Distance Correlation, IEEE Transactions on Medical Imaging, Dec.14, 2017, DOI: 10.1109/TMI.2017.2783244, PMID: 29990017, PMCID: PMC6043419[Available on 2019-06-13]
  124. Biao Cai, Pascal Zille, Julia M. Stephen, Tony W. Wilson, Vince D. Calhoun, Yu Ping Wang, Estimation of dynamic sparse connectivity patterns from resting state fMRI, IEEE Transactions on Medical Imaging, 2018 May; 37(5):1224-1234. DOI: 10.1109/TMI.2017.2786553, PMID: 29727285
  125. Jian Fang, Ji-Gang Zhang, Hong-Wen Deng, and Yu-Ping Wang, Joint Detection of Associations between DNA Methylation and Gene Expression from Multiple Cancers, IEEE Journal of Biomedical and Health Informatics, Dec. 18, 2017. DOI: 10.1109/JBHI.2017.2784621, PMID: 29990049
  126. Alexej Gossmann, Shaolong Cao, Damian Brzyski, Lan-Juan Zhao, Hong-Wen Deng, and Yu-Ping Wang, A sparse regression method for group-wise feature selection with false discovery rate control, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2018 Jul-Aug; 15(4):1066-1078, DOI: 10.1109/TCBB.2017.2780106, PMID: 29990279
  127. Ashad Alam, Kenji Fukumizu, Yu-Ping Wang, Influence Function and Robust Variant of Kernel Canonical Correlation Analysis, Neurocomputing, Volume 304, 23 August 2018, Pages 12-29, https://doi.org/10.1016/j.neucom.2018.04.008
  128. Ashad Alam, Vince D. Calhoun, Yu-Ping Wang, Identifying outliers using multiple kernel canonical correlation analysis with application to imaging genetics, Computational Statistics & Data Analysis, September 2018, Volume 125, Pages 70-85, DOI: https://doi.org/10.1016/j.csda.2018.03.013
  129. Md. Ashad Alama, Hui-Yi Lin, Hong-Wen Deng, Vince D. Calhoun, and Yu-Ping Wang, A Kernel Machine Method for Detecting Higher Order Interactions in Multimodal Datasets: Application to Schizophrenia, Journal of Neuroscience Methods, 2018 Nov 1; 309:161-174. doi: 10.1016/j.jneumeth.2018.08.027, PMID: 30184473
  130. Li Chunlei, Liu Chaodie, Gao Guangshuai, Liu Zhoufeng, Yu-Ping Wang, Robust low-rank decomposition of multi-channel feature matrices for fabric defect detection, Multimedia Tools and Applications, in press, 2018, pp 1–19, DOI: 10.1007/s11042-018-6483-6.
  131. Chao Xu, Jian Fang, Hui Shen, Yu-Ping Wang and Hong-Wen Deng, EPS-LASSO: Test for High-Dimensional Regression Under Extreme Phenotype Sampling of Continuous Traits, Bioinformatics, 2018 Jun 15; 34(12):1996-2003. doi: 10.1093/bioinformatics/bty042. PMID: 29385408
  132. Ashkan Faghiri, Julia M. Stephen, Yu-Ping Wang, Tony W. Wilson, and Vince D. Calhoun, Changing brain connectivity dynamics: From early childhood to adult, Human Brain Mapping, 2018 Mar;39(3):1108-1117. DOI: 10.1002/hbm.23896, PMID: 29205692, PMCID: PMC5807176[Available on 2019-03-01]
  133. Pascal Zille, Vince D. Calhoun, Yu-Ping Wang, Enforcing Co-expression Within a Brain-Imaging Genomics Regression Framework, IEEE Transactions on Medical Imaging, 28 June 2017, Page(s): 1-1, DOI: 10.1109/TMI.2017.2721301, PMID: 28678703
  134. Pascal Zille, Vince D. Calhoun, Julia M. Stephen, Tony W. Wilson, Yu-Ping Wang, Fused estimation of sparse connectivity patterns from rest fMRI: Application to comparison of children and adult brains, IEEE Transactions on Medical Imaging, 2018 Oct; 37(10):2165-2175. DOI: 10.1109/TMI.2017.2721640, PMID: 28682248, PMCID: PMC5785555
  135. Wenxing Hu, Dongdong Lin, Shaolong Cao, Jing Yu Liu, Jiayu Chen, Vince Calhoun, Yu-Ping Wang, Adaptive sparse multiple canonical correlation analysis with application to imaging (epi)genomics study of schizophrenia, IEEE Trans. Biomedical Engineering, 2018 Feb; 65(2):390-399, DOI: 10.1109/TBME.2017.2771483, PMID: 29364120, PMCID: PMC5826588[Available on 2019-02-01]
  136. Su-Ping Deng, Wenxing Hu, Vince D. Calhoun, Yu-Ping Wang, Integrating Imaging Genomic Data in the Quest for Biomarkers for Schizophrenia Disease, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2018 Sep-Oct; 15(5):1480-1491. doi: 10.1109/TCBB.2017.2748944, PMID: 28880187, PMCID: PMC6207076[Available on 2019-09-01]
  137. Li J., Lin D, and Wang YP, Segmentation of Multicolor Fluorescence In-Situ Hybridization (M-FISH) Images Using an Improved Fuzzy C-Means Clustering Algorithm by Incorporating both Spatial and Spectral Information, Journal of Medical Imaging, 2017 Oct; 4(4):044001. doi: 10.1117/1.JMI.4.4.044001. PMID: 29021991, PMCID: PMC5633778
  138. Su-Ping Deng, Wenxing Hu, Vince D. Calhoun, Yu-Ping Wang, Schizophrenia Prediction Using Integrated Imaging Genomic Networks, Advances in Science, Technology and Engineering Systems Journal, Vol.2, No.3, 702-710(2017), DOI: 10.25046/aj020390
  139. Dongdong Lin, Jiayu Chen, Stefan Ehrlich, Juan R. Bustillo, Nora Perrone-Bizzozero, Esther Walton, Vincent P. Clark, Yu-Ping Wang, Jing Sui, Yuhui Du, Beng C. Ho, Charles S. Schulz, Vince D. Calhoun,Jingyu Liu, Cross-Tissue Exploration of Genetic and Epigenetic Effects on Brain Gray Matter in Schizophrenia. Schizophrenia Bulletin, 2018 Feb 15; 44(2):443-452. doi: 10.1093/schbul/sbx068, PMID: 28521044, PMCID: PMC5814943[Available on 2019-02-15]
  140. Song J, Yang Y, Mauvais-Jarvis F, Wang YP, Niu T., KCNJ11, ABCC8 and TCF7L2 polymorphisms and the response to sulfonylurea treatment in patients with type 2 diabetes: a bioinformatics assessment. BMC Med Genet. 2017 Jun 6; 18(1):64. doi:10.1186/s12881-017-0422-7. PubMed PMID: 28587604; PMCID: PMC5461698
  141. He H, Lin D, Zhang J, Wang YP, Deng HW. Comparison of statistical methods for subnetwork detection in the integration of gene expression and protein interaction network. BMC Bioinformatics. 2017 Mar 3; 18(1):149. doi: 10.1186/s12859-017-1567-2. PMID: 28253853, PMCID: PMC5335754
  142. Keith Dillon, Vince Calhoun, and Y.-P. Wang, A Robust Sparse-Modeling Framework for Estimating Schizophrenia Biomarkers from fMRI. Journal of Neuroscience Methods, 2017 Jan 30; 276:46-55, DOI:http://dx.doi.org/10.1016/j.jneumeth.2016.11.005, PMID: 27867012, PMCID: PMC5237618
  143. Zhang R, Strong MJ, Baddoo M, Lin Z, Wang YP, Flemington EK*, Liu YZ*, Interaction of Epstein-Barr virus genes with human gastric carcinoma transcriptome. Oncotarget, 2017 Jun 13;8(24):38399-38412, DOI: 10.18632/oncotarget.16417, PMID: 28415594 PMCID: PMC5503541
  144. Jian Fang, Dongdong Lin, Charles Schultz, Zongben Xu, Vince Calhoun and Yu-Ping Wang, Joint sparse canonical correlation analysis for detecting differential imaging genetics modules. Bioinformatics, 2016 Nov 15; 32(22):3480-3488, doi: 10.1093/bioinformatics/btw485, PMID: 27466625, PMCID: PMC5181564. [PDF file]
  145. S.P. Deng, D. S. Huang, S. Cao and Y.-P. Wang, Identifying Stages of Kidney Renal Cell Carcinoma by Combining Gene Expression and DNA Methylation Data, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2017 Sep-Oct; 14(5):1147-1153, DOI: 10.1109/TCBB.2016.2607717, PMID: 28113675, PMCID: PMC5515692. [PDF file]
  146. P. Zhou, Y.-P. Wang, H. Cao, and Lydia C Manor, Literature Data Mining and Enrichment Analysis Reveal A Genetic Network of 423 Genes for Renal Cancer, Med One 2016;1(3):1; DOI:10.20900/mo.20160010 [PDF file]
  147. Keith Dillon, Y. Fainman, and Y.-P. Wang, Computational Estimation of Resolution in Reconstruction Techniques Utilizing Sparsity, Total Variation, and Non-negativity, Journal of Electronic Imaging, 25(5), 053016(Sep 23, 2016). doi:10.1117/1.JEI.25.5.053016
  148. Dongdong Lin, Jigang Zhang, Jingyao Li, Chao Xu, Hong-wen Deng, Yu-Ping Wang, An integrative imputation method based on multi-omics datasets. BMC Bioinformatics. 2016 Jun 21; 17:247, doi: 10.1186/s12859-016-1122-6, PMID: 27329642, PMCID: PMC4915152. [PDF file]
  149. S. Cao, H. Qin, A. Gossamn, H.-W. Deng and Yu-Ping Wang, Unified tests for fine scale mapping and identifying sparse high-dimensional sequence associations. Bioinformatics, 2016 Feb 1;32(3):330-7. doi: 10.1093/bioinformatics/btv586, PMID: 26458888, PMCID: PMC5006306. [PDF file]
  150. M. Wang, T.Z. Huang, J. Li and Yu-Ping Wang, A Patch-Based Tensor Decomposition Algorithm for M-FISH Image Classification, Cytometry A, 2017 Jun; 91(6):622-632. doi: 10.1002/cyto.a.22864, PMID: 27144669. [PDF file]
  151. Keith Dillon and Y.-P. Wang, Imposing Uniqueness to Achieve Sparsity, Signal Processing, 2016 Jun 1; 12:1-8. doi: 10.1016/j.sigpro.2015.12.009, PMID: 26778868, PMCID: PMC4710964. [PDF file]
  152. J. Duan, C. Soussen, D. Brie, J. Idier, M. Wan and Y.-P. Wang, Generalized LASSO with under-determined regularization matrices, Signal Processing, 2016 Oct; 127:239-246. doi: 10.1016/j.sigpro.2016.03.001, PMID: 27346902, PMCID: PMC4917299 [PDF file]
  153. Lan S, Wang L, Song Y, Wang YP, Yao L, Sun K, Xia B, Zongben X, Improving Separability of Structures with Similar Attributes in 2D Transfer Function Design. IEEE Trans Vis Comput Graph, 2017 May; 23(5):1546-1560. doi: 10.1109/TVCG.2016.2537341, PMID: 26955038 [PDF file]
  154. Hao He, Shaolong Cao, Tianhua Niu, Yu Zhou, Lan Zhang, Yong Zeng, Wei Zhu, Yu-Ping Wang, and Hong-wen Deng, Network-Based Meta-Analyses of Associations of Multiple Gene Expression Profiles with Bone Mineral Density Variations in Women, PLOS ONE, 2016 Jan 25; 11(1):e0147475, doi:10.1371/journal.pone.0147475, PMID: 26808152, PMCID: PMC4726665 [PDF file]
  155. Liu YZ, Maney P, Puri J, Zhou Y, Baddoo M5, Strong M, Wang YP, Flemington E, Deng HW., RNA-sequencing study of peripheral blood monocytes in chronic periodontitis, Gene, 2016 May 1;581(2):152-60. doi: 10.1016/j.gene.2016.01.036. PMID: 26812355, PMCID: PMC4767619. [PDF file]
  156. J. Duan, J. Zhang, M. Wan, H. W. Deng, and Yu-Ping Wang, A sparse model based detection of copy number variations from exome sequencing data, IEEE Trans. Biomedical Engineering, 2016 Mar; 63(3)pp. 496-505. doi: 10.1109/TBME.2015.2464674, PMID: 26258935, PMCID: PMC4808620. [PDF file]
  157. Chen Qiao, Wen-Feng Jing, Jian Fang, and Yu-Ping Wang, The general critical analysis for continuous-time UPPAM recurrent neural networks, Neurocomputing, 2016 Jan 29; 175(Pt A):40-46. doi: 10.1016/j.neucom.2015.09.103, PMID: 26858512, PMCID: PMC4742343. [PDF file]
  158. Niu T, Liu N, Zhao M, Xie G, Zhang L, Li J, Pei YF, Shen H, Fu X, He H, Lu S, Chen XD, Tan LJ, Yang TL, Guo Y, Leo PJ, Duncan EL, Shen J, Guo YF, Nicholson GC, Prince RL, Eisman JA, Jones G, Sambrook PN, Hu X, Das PM, Tian Q, Zhu XZ, Papasian CJ, Brown MA, Uitterlinden AG, Wang YP, Xiang S, Deng HW. Identification of a Novel FGFRL1 MicroRNA Target Site Polymorphism for Bone Mineral Density in Meta-Analyses of Genome-Wide Association Studies. Hum Mol Genet. 2015 Aug 15; 24(16):4710-27. doi: 10.1093/hmg/ddv144. Epub 2015 May 4. PMID: 25941324, PMCID: PMC4512621. [PDF file]
  159. Wenlong Tang, Chao Xu, Yu-Ping Wang, Hong-Wen Deng, Ji-Gang Zhang, MicroRNA–mRNA interaction analysis to detect potential dysregulation in complex diseases, Network Modeling Analysis in Health Informatics and Bioinformatics, First Online: 10 January 2015. vol. 4, no. 1. doi: 10.1007/s13721-014-0074-x [PDF file]
  160. Dongdong Lin, H. Cao, Vince D. Calhoun, and Yu-Ping Wang, Sparse models for correlative and integrative analysis of imaging and genetic data, J. Neuroscience Methods, Volume 237, 2014 Nov 30; 237:69-78. doi: 10.1016/j.jneumeth.2014.09.001. PMID: 25218561, PMCID: PMC4194220. [PDF file]
  161. Xu C, Zhang J, Wang YP, Deng HW, and Li J., Characterization of human chromosomal material exchange with regard to the chromosome translocations using next-generation sequencing data, Genome Biol Evol. 2014 Oct 27; 6(11):3015-24. doi: 10.1093/gbe/evu234. PMID: 25349267, PMCID: PMC4255766. [PDF file]
  162. Dongdong Lin, Jigang Zhang, Jingyao Li, hong-wen Deng, Yu-Ping Wang, Integrative analysis of multiple diverse omics datasets by sparse group multitask regression, Frontiers in Cell and Developmental Biology, section Systems Biology, 2014 Oct 27; 2:62, doi: 10.3389/fcell.2014.00062. PMID: 25364766, PMCID: PMC4209817. [PDF file]
  163. Shaolong Cao, Huaizhen Qin, Hong-Wen Deng and Yu-Ping Wang, A unified sparse representation for sequence variant identification for complex traits. Genetic epidemiology. 2014 Dec; 38(8):671-9. doi: 10.1002/gepi.21849. PMID: 25195875, PMCID: PMC4236284. [PDF file]
  164. J. Duan, J. Zhang, M. Wan, H. W. Deng, and Yu-Ping Wang, Population clustering based on copy number variations detected from next generation sequencing data, Journal Bioinformatics and Computational Biology, 2014 Aug;12(4):1450021. doi: 10.1142/S0219720014500218, PMID: 25152046 PMCID: PMC4504183. [PDF file]
  165. He H, Zhang L, Li J, Wang YP, Zhang JG, Shen J, Guo YF, Deng HW., Integrative analysis of GWASs, human protein interaction and gene expression identified gene modules associated with BMDs, J Clin Endocrinol. Metab., Impact factor: 6.31, 2014 Nov; 99(11):E2392-9. doi: 10.1210/jc.2014-2563. PMID: 25119315, PMCID: PMC4223444. [PDF file]
  166. Zhang L, Pei YF, Lin, Y., Wang YP, and Deng HW, FISH: Fast and Accurate Diploid Genotype Imputation via Segmental Hidden Markov Model, Bioinformatics. Impact factor: 5.323, doi: 10.1093/bioinformatics/btu480 2014 Jul 1;30(13):1876-83. PMID: 24618466, PMCID: PMC4071209. [PDF file]
  167. L. Wang, Lisheng Wang, Pai Wang, Liuhang Cheng, Yu Ma, Shenzhi Wu, Yuping Wang, Zongben Xu, Detection and Reconstruction of Implicit Boundary Surface by Expanding Adaptively Its A Small Surface Patch in 3D Image, IEEE Transactions on Visualization and Computer Graphics, 2014 Nov;20(11):1490-506. doi: 10.1109/TVCG.2014.2312015. PMID: 26355329. [PDF file]
  168. Hongbao Cao, Junbo Duan, Dongdong Lin, Yin Yao Shugart, Vince Calhoun, and Yu-Ping Wang, Sparse Representation Based Biomarker Selection for Schizophrenia with Integrated Analysis of fMRI and SNPs, NeuroImage, Impact factor: 6.252, 2014 Nov 15; 102P1:220-228. doi: 10.1016/j.neuroimage.2014.01.021. PMID: 24530838, PMCID: PMC4130811. [PDF file]
  169. J. Duan, H. W. Deng, and Y. P. Wang, Common copy number variation detection from multiple sequenced samples, IEEE Trans. Biomedical Engineering, 2014 Mar; 61(3):928-37. doi: 10.1109/TBME.2013.2292588, PMID: 24557694, PMCID: PMC4165854. [PDF file]
  170. Zhang L, Choi HJ, Estrada K, Leo PJ, Li J, Pei YF, Zhang Y, Lin Y, Shen H, Liu YZ, Liu Y, Zhao Y, Zhang JG, Tian Q, Wang YP, Han Y, Ran S, Hai R, Zhu XZ, Wu S, Yan H, Liu X, Yang TL, Guo Y, Zhang F, Guo YF, Chen Y, Chen X, Tan L, Zhang L, Deng FY, Deng H, Rivadeneira F, Duncan EL, Lee JY, Han BG, Cho NH, Nicholson GC, McCloskey E, Eastell R, Prince RL, Eisman JA, Jones G, Reid IR, Sambrook PN, Dennison EM, Danoy P, Yerges-Armstrong LM, Streeten EA, Hu T, Xiang S, Papasian CJ, Brown MA, Shin CS, Uitterlinden AG, Deng HW., Multistage genome-wide association meta-analyses identified two new loci for bone mineral density, Hum Mol Genet. 2014 Apr 1; 23(7):1923-33. doi: 10.1093/hmg/ddt575. IF=7.692, PMID: 24249740, PMCID: PMC3943521. [PDF file]
  171. Pei YF, Zhang L, Papasian CJ, Wang YP, Deng HW, On individual genome-wide association studies and their meta-analysis, Hum Genet. 2014 Mar; 133(3):265-79. doi: 10.1007/s00439-013-1366-4. IF=5.047, PMID: 24114349, PMCID: PMC4127980. [PDF file]
  172. Dongdong Lin, Jigang Zhang, Jinyao Li, Vince D. Calhoun, Hong-Wen Deng and Yu-Ping Wang, Group sparse canonical correlation analysis for genomic data integration, BMC Bioinformatics, 2013, vol.14, no. 150, doi: 10.1186/1471-2105-14-245. [PDF file]
  173. H. Cao, J. Duan, D. Lin, V. Calhoun, Y. Wang, Integrating fMRI and SNP data for biomarker identification for Schizophrenia with a sparse representation based variable selection method, BMC Medical Genomics, 2013, 6(Suppl 3):S2 (11 November 2013). doi: 10.1186/1755-8794-6-S3-S2. IF=3.47 [PDF file]
  174. J. Li, D. Lin, H. Cao, Y. Wang, Classification of Multicolor Fluorescence In-Situ Hybridization (M-FISH) Image Using a Structure Based Sparse Representation Model, BMC Systems Biology, BMC Systems Biology 2013, 7(Suppl 4):S5 doi:10.1186/1752-0509-7-S4-S5, IF=2.98
  175. Dongdong Lin, Vince D. Calhoun, and Yu-Ping Wang, Correspondence between fMRI and SNP Data by Group Sparse Canonical Correlation Analysis, Medical Image Analysis, 2013, doi:10.1016/j.media.2013.10.010. IF=4.087 [PDF file]
  176. J. Duan, J. Zhang, H. W. Deng, and Y. P. Wang, CNV-TV: A robust method to discover copy number variation from short sequencing reads, BMC Bioinformatics, 2013, vol.14, no. 150, doi:10.1186/1471-2105-14-150 [PDF file]
  177. W. Tang, J. Duan, J. Zhang, and Y. P. Wang, Subtyping glioblastoma by combining miRNA and mRNA expression data using compressed sensing-based approach, EURASIP J Bioinform Syst Biol. 2013 Jan 14;2013(1):2. doi: 10.1186/1687-4153-2013-2. [PDF file]
  178. J. Duan, J. Zhang, H. W. Deng, and Y. P. Wang, Comparative studies of copy number variation detection methods for next-generation sequencing technologies, PLoS One, vol.8, no.3. doi: 10.1371/journal.pone.0059128. Published: March 20, 2013. [PDF file]
  179. J. Duan, C. Soussen, D. Brie, J. Idier and Y.-P. Wang, On LARS/homotopy equivalence conditions for over-determined LASSO, IEEE Signal Processing Letters, 19(12), 2012. doi: 10.1109/LSP.2012.2221712. [PDF file]
  180. Hongbao Cao, Marilyn Li, H.W Deng and Yu-Ping Wang, Classification of multicolor fluorescence in-situ hybridization (M-FISH) images with sparse representation, IEEE Trans. Nano Biosciences, 2012 Jun;11(2):111-8. doi: 10.1109/TNB.2012.2189414. [PDF file]
  181. Hongbao Cao, Shufeng Lei, H.W Deng and Yu-Ping Wang, Identification of genes for complex diseases using integrated analysis of multiple types of genomic data, PLOS ONE, Sept., 2012, 7(9):1-8. doi:10.1371/journal.pone.0042755. [PDF file]
  182. Hongbao Cao and Yu-Ping Wang, Segmentation of M-FISH images for improved classification of chromosomes with an adaptive fuzzy c-means clustering algorithm, IEEE Trans. Fuzzy Systems, 2011, 20(1): 1-8. doi: 10.1109/ISBI.2011.5872671. [PDF file]
  183. Wenlong Tang, Hongbao Cao, Jigang Zhang, Junbo Duan and Yu-Ping Wang, Subtyping of Glioma by Combining Gene Expression and CNVs Data Based on a Compressive Sensing Approach, Medical Advancements in Genetic Engineering, vol. 1, no. 1, 2012. doi: 10.4172/2169-0111.1000101. [PDF file]
  184. Hongbao Cao and Yu-Ping Wang, Integrated Analysis of Gene Expression and Copy Number Data using Sparse Representation Based Clustering Model, Int. Journal of Computers and Their Applications, July, 2012. [PDF file]
  185. Wenlong Tang, Hongbao Cao, and Yu-Ping Wang, A Compressive Sensing Method for Subtyping of Leukemia with Gene Expression Analysis Data, Journal of Bioinformatics and Computational Biology, vol 9, no. 5, 2011. [PDF file]
  186. J. Sheng, V. Calhoun, H.W. Deng and Y.-P Wang, An integrated analysis of gene expression and copy number data on gene shaving using independent component analysis, IEEE Trans. Computational Biology and Bioinformatics, 2011 Nov-Dec;8(6):1568-79. doi: 10.1109/TCBB.2011.71. [PDF file]
  187. Shengnan Lu, Yu-Ping Wang, Huansheng Song A high accurate vehicle speed estimation method, Soft Computing, First Online: 09 April 2019; pp 1-9; DOI: https://doi.org/10.1007/s00500-019-03965-w
  188. J. Chen, Ayten Yiğiter, Y.-P. Wang, and H.-W. Deng, A Bayesian Analysis for Identifying DNA Copy Number Variations Using a Compound Poisson Process, EURASIP J Bioinform Syst Biol. 2010; 2010(1): 268513. Published online 2010 Aug 17. doi: 10.1155/2010/268513. [PDF file]
  189. Yu-Ping Wang, Multiscale genomic imaging informatics, IEEE Signal Processing Magazine, Nov.-Dec issue, pp. 169-172, 2009. doi: 10.1109/MSP.2009.934185. [PDF file]
  190. Jie Chen and Yu-Ping Wang, A statistical model-based approach for the identification of DNA copy number changes in array CGH datasets, IEEE Trans. Computational Biology and Bioinformatics, 6(4), Oct-Dec issue, 2009. doi: 10.1109/TCBB.2008.129 [PDF file]
  191. Ranganathan Parthasarathy, Ganesh Thiagarajan, Xiaomei Yao, Yu-Ping Wang, Paulette Spencer and Yong Wang, Application of Univariate and Multivariate Analyses in Micro-Raman Imaging to Unveil Structural/Chemical Features of the Adhesive/Dentin Interface, J. of Biomedical Optics, 2008 Jan-Feb;13(1):014020. doi: 10.1117/1.2857402. [PDF file]
  192. F. Zhang, Yu-Ping Wang, and HW Deng, Comparison of Population-Based Association Study Methods Correcting for Population Stratification, PLoS ONE, 3(10):1-7, 2008. doi: 10.1371/journal.pone.0003392. [PDF file]
  193. Y. Guo, J. Li, A J. Bonham, Y.-P. Wang, and HW Deng, Gains in power for exhaustive analyses of haplotypes using variable-sized sliding window strategy: a comparison of association-mapping strategies, Eur. J. Human Genetics, Published online 2008 Dec 17. doi: 10.1038/ejhg.2008.244. [PDF file]
  194. Y.-P.Wang, M. Gunampally, J. Chen, D. Bittel, M. Butler and W.-W. Cai, A Comparison of Fuzzy Clustering Approaches for Quantification of Microarray Gene Expression, Journal of VLSI Signal Processing Special Issue on Machine Learning for Microarray and Sequence Analysis, 50: 305-320, 2008. doi: 10.1007/s11265-007-0123-0. [PDF file]
  195. Yu-Ping Wang, Husain Ragib, and Chi-Ming Huang, A wavelet approach for the identification of axonal synaptic varicosities from microscope images, IEEE Trans. Information Technology in Biomedicine, May, 11(3): 296-304, 2007. doi: 10.1109/TITB.2006.884370. [PDF file]
  196. Yu-Ping Wang and Ashok Dandpat, A Hybrid Approach of Using Wavelets and Fuzzy Clustering for Classifying Multi-spectral Florescence in Situ Hybridization Images, Int. Journal of Biomedical Imaging, vol. 2006, pp. 1-11, 2006. doi: 10.1155/IJBI/2006/54532. [PDF file]
  197. P.Sivakumar, A.Czirok, B.J.Rongish, V.P.Divakara, Y.-P.Wang and S.L.Dallas, New Insights into Extracellular Matrix Assembly and Reorganization from Dynamic Imaging of Extracellular Matrix Proteins in Living Osteoblasts, Journal of Cell Science, 119:1350-1360, 2006. doi: 10.1242/jcs.02830. [PDF file]
  198. Huang, C. Titus, J.A. Wang, Y. and Huang, R. Information Coding Capacity of Cerebellar Parallel Fibers, Brain Research Bulletin, 2006 Jun 15;70(1):49-54. Epub 2006 Feb 10. doi: 10.1016/j.brainresbull.2006.01.007. [PDF file]
  199. Yu-Ping Wang, Y. Wang and P. Spencer, Fuzzy Clustering of Raman Spectral Imaging Data with a Wavelet-Based Noise Reduction Approach, Applied Spectroscopy, 2006 Jul;60(7):826-32. doi: 10.1366/000370206777886964. [PDF file]
  200. Yu-Ping Wang and Ken Castleman, Automated Registration of Multi-Color Fluorescence In Situ Hybridization (M-FISH) Images for Improving Color Karyotyping, Cytometry, Part A, 2005 Apr;64(2):101-9. doi: 10.1002/cyto.a.20116. [PDF file]
  201. Yu-Ping Wang, J. Chen, Q. Wu and Ken Castleman, Fast frequency estimation by zero-crossings of differential spline wavelet transform, EURASIP Journal on Applied Signal Processing, 2005(8): 1251-1260, May, 2005. doi: 10.1117/12.615968. [PDF file]
  202. Yu-Ping Wang and Wei-Wen Cai, Genetic imaging: where imaging science meets cytogenetic research, Biophotonics Magazine, Nov., 2004.
  203. Yu-Ping Wang, Q. Wu, Ken. Castleman, and Z. Xiong , Chromosome Image Enhancement Using Multiscale Differential Operators, IEEE Trans. Medical Imaging, 2003 May;22(5):685-93. doi: 10.1109/TMI.2003.812255. [PDF file]
  204. Z. Liu, Z. Xiong, Q. Wu, Y. Wang, and K. Castleman, Cascaded differential and wavelet compression of chromosome images, IEEE Trans. on Biomedical Engineering, 2002 Apr;49(4):372-83. doi: 10.1109/10.991165. [PDF file]
  205. Yu-Ping Wang, Y. Chen, A. A. Amini, Fast LV Motion Estimation using Subspace Approximation Techniques, IEEE Trans. Medical Imaging, 2001 Jun;20(6):499-513. doi: 10.1109/42.929616. [PDF file]
  206. Yu-Ping Wang, S. L. Lee, Scale-space derived from B-splines, IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 20, no. 10, Oct. 1998, pp.1050-1065. doi: 10.1109/34.722612. [PDF file]
  207. Yu-Ping Wang, Qu Ruibin, Initialization and inner product computation of wavelet transform using interpolatory subdivision scheme, IEEE Trans. Signal Processing, vol. 47, no. 3, p. 817, 1999. doi: 10.1109/78.747795. [PDF file]
  208. Yu-Ping Wang, S. L. Lee, K. Torachi, Multiscale curvature based shape representation using B-spline wavelets, IEEE Trans. Image Processing, 1999;8(11):1586-92. doi: 10.1109/83.799886. [PDF file]
  209. Yu-Ping Wang, Image representations using multiscale differential operators, IEEE Trans. Image Processing, 1999;8(12):1757-71. doi: 10.1109/83.806621. [PDF file]
  210. Yu-Ping Wang, Qu Ruibin, Fast implementation of scale-space by interpolatoy subdivision scheme, IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 21, no. 9, 1999 pp.1050-1065. doi: 10.1109/34.790434. [PDF file]
  211. Jun-Feng Guo, Yuan-Long Cai, Yu-Ping Wang, Morphology-Based Interpolation for 3-D Medical Image Reconstruction, Computerized Medical Imaging and Graphics, vol.19, no.3, pp. 267-279, 1995. doi: 10.1016/0895-6111(95)00007-D. [PDF file]
  212. Yu-Ping Wang and Gui-Zhong Liu, Computation of Continuous Wavelet Transform by Interpolation, Journal of Electronic Science and Technology, no.3. pp. 42-44, September 1993.
  213. Long Gong ,Yu-Ping Wang and Zheng Tan, A Zero-Crossing Edge Detection Operator with Variable Scale and Orientation, Journal of Data Acquisition and Processing, vol.10, no.3, pp.175-180, 1995.
  214. Jin-Feng Guo, Yuan-Long Cai and Yu-Ping Wang, Investigation of Interpolation Methods for Medical 3D Reconstruction, Computerized Tomography: Theory and Applications, vol.3, no.4, pp. 7-11, 1994.
  215. Chao-Wei Yuan, Zhao-Yong You and Yu-Ping Wang, A Novel Algorithm of Inverse Radon Transform, J. of Electronic Science and Technology, No.3. pp. 49-54, September 1993.
  216. Yu-Hua Peng,Ya-Xun Liu,Yu-Ping Wang, Wen-Bing Wang, The Application Of Wavelet Transform to Time-Frequency Analysis of Electromagnetic Backscatter Signals, Acta Electronica Sinica, vol.23, no.9, pp.109-111,1995.
  217. Yu-Ping Wang, Yuan-Long Cai, Zhong-xing Geng and Rui Feng, Application of Wavelet Packet Transform to Seismic Signal Processing, to appear in Acta Seismology Sinica, 1995.
  218. Yu-Ping Wang and Yuan-Long Cai, A Type of B-Spline Wavelet and the Associated Fast Algorithms, to appear at Signal Processing(Chinese).
  219. Jiehui Yuan, Yu-Ping Wang, and Yuan-Long Cai, The Modeling and Extraction of Visual Primary Components in Images, China journal of Image and Graphics, Vol.2, No.8-9, pp.594-598, Sep. 1997.
  220. Yu-Ping Wang, A Wavelet is Creating Great Waves, Science (Chinese), vol.47, no.4, 1995.
  221. Yu-Ping Wang, Yuan-Long Cai and Jun-Feng Guo, Construction of Wavelet Packet Bases and Their Properties, Journal of Xi'an Jiaotong University, vol.29, no.4, pp. 26-31, 1995.
  222. Yu-Ping Wang and Yuan-Long Cai, Multiscale B-Spline Wavelet for Edge Detection, Science in China, Ser. A, Vol.38, No.4, pp. 499-512, 1995.
  223. Yu-Ping Wang and Yuan-Long Cai, An Overview of Wavelet Transform to Signal Processing, Radio Engineering, vol.24, no.3, pp. 11-19, 1994.
  224. Yu-Ping Wang and Yuan-Long Cai, Filtering Based on Wavelet Transform, Information and Control, 1996.

Conference papers (peer reviewed)

  1. P. Zille, V. Calhoun and Y. P. Wang, Enforcing Co-expression in Multimodal Regression Framework, Pacific Symposium on Biocomputing (PSB) 2017, January 3-7, 2017, The Big Island of Hawaii.
  2. P. Zille, V. Calhoun, J. Stephen, T. Wilson, and Y.-P. Wang, Fused estimation of sparse connectivity patterns from rest fMRI, ICASSP’17, March 5-9, New Orleans.
  3. M. Wang, T.-Z. Huang, V. Calhoun, J. Fang, and Y.-P. Wang, Integration of multiple genomic imaging data for the study of schizophrenia using joint nonnegative matrix factorization, ICASSP’17, March 5-9, New Orleans.
  4. O. Richfield, M.A. Alam, V. Calhoun and Y.P. Wang, Learning Schizophrenia Imaging Genetics Data Via Multiple Kernel Canonical Correlation Analysis, 2016 IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM 2016), Dec. 15-18, Shenzhen, China.
  5. Md Ashad Alam, Vince Calhoun and Yu-Ping Wang, Influence Function of Multiple Kernel Canonical Analysis to Identify Outliers in Imaging Genetics Data, ACM-BCB 2016, Seattle, WA, October 2-5, 2016
  6. Md Ashad Alam, Osamu Komori, Vince Calhoun and Yu-Ping Wang, Robust Kernel Canonical Correlation Analysis to Detect Gene-Gene Interaction for Imaging Genetics Data, ACM-BCB 2016, Seattle, WA, October 2-5, 2016
  7. K. Dillion and Y.-P Wang, An Image Resolution Perspective on Functional Activity Mapping, the 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC’16), Orlando, FL, USA during August 17-20, 2016
  8. K. Dillion and Y.-P Wang, On Efficient Meta-Filtering of Big Data, the 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC’16), Orlando, FL, USA during August 17-20, 2016
  9. S. P. Deng, D. Lin, V. Calhoun and Y.-P Wang, Predicting Schizophrenia by Fusing Networks from SNPs, DNA Methylation and fMRI Data, the 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC’16), Orlando, FL, USA during August 17-20, 2016
  10. W. Hu, V. Calhoun and Y.-P Wang, Integration of SNP-FMRI-Methylation Data with Sparse Multi-CCA for Schizophrenia Study, the 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC’16), Orlando, FL, USA during August 17-20, 2016
  11. Jian Fang, Dongdong Lin, Zongben Xu, Vince Calhoun and Yu-Ping Wang, Joint Sparse Canonical Correlation Analysis for Detecting Multivariate Differential Imaging Genetics Associations, ISMB 2016 at Orlando, Florida, USA.
  12. Chen Qiao, and Yu-Ping Wang, The effective diagnosis of schizophrenia by using 4-layer RBMs deep networks, the 2015 IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM 2015), Washington DC, Nov.9-12, 2015.
  13. Jingyao Li, Dongdong Lin, and Yu-Ping Wang, Segmentation of Multicolor Fluorescence In-Situ Hybridization (M-FISH) Image Using an Improved Fuzzy C-Means Clustering Algorithm incorporating Both Spatial and Spectral Information, the 2015 IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM 2015), Washington DC, Nov.9-12, 2015.
  14. Shaolong Cao, Huaizhen Qin, Alexej Gossmann, Hong-Wen Deng and Yu-Ping Wang. Unified tests for fine scale mapping and identifying sparse high-dimensional sequence associations, the 6th ACM Conference on Bioinformatics, Computational Biology and Biomedical Informatics (ACM-BCB’15), Atlanta, GA, Sept. 9-12, 2015.
  15. Alexej Gossmann, Shaolong Cao and Yu-Ping Wang. Identification of significant genetic variants via SLOPE, and its extension to Group SLOPE, the 6th ACM Conference on Bioinformatics, Computational Biology and Biomedical Informatics (ACM-BCB’15), Atlanta, GA, Sept. 9-12, 2015.
  16. Junbo Duan, Charles Soussen, David Brie, Jérôme IDIER, Yu-Ping Wang, Mingxi Wan, An optimal method to segment piecewise Poisson distributed signals with application to sequencing data, the IEEE Engineering in Medicine and Biology Society (EMBC'15) in MiCo, Milano Conference Center, Milano, Italy on August 25-29, 2015.
  17. Dongdong LIN, Jigang Zhang, Jingyao Li, Vince Calhoun, Yu-Ping Wang, Detection of genetic factors associated with multiple correlated imaging phenotypes by a sparse regression model, International Symposium on Biomedical Imaging (ISBI 2015), New York City, USA, April 16-19, 2015.
  18. S. Cao, H. Qin, J. Li, H. W. Deng, and Y. P. Wang, " Scaled Sparse High Dimensional Tests for Localizing Sequence Variants, the 5th ACM Conference on Bioinformatics, Computational Biology and Biomedical Informatics (ACM BCB), New port Beach, CA, Sep. 19-23, 2014.
  19. Dongdong Lin,Hao He,Jingyao Li,Hong-Wen Deng,Vince D. Calhoun,Yu-Ping Wang, Network-based investigation of genomic modules associated with functional brain network in schizophrenia, 2013 IEEE International Conference on Bioinformatics and Biomedicine (BIBM13), Shanghai, China, Dec. 18-21, 2013.
  20. S. Cao, H. Qin, H. W. Deng, and Y. P. Wang, "A generalized sparse regression model with adjustment of pedigree structure for variant detection from next generation sequencing data," presented at the ACM Conference on Bioinformatics, Computational Biology and Biomedical Informatics (ACM BCB), Washington DC, 2013.
  21. Hongbao Cao, Junbo Duan Dongdong Lin, Vince Calhoun, and Yu-Ping Wang, Sparse representation based biomarker selection for schizophrenia with integrative analysis of fMRI and SNP data, International Symposium on Biomedical Imaging (ISBI 2013), San Francisco, CA, USA, April 8-11, 2013
  22. Jingyao Li, Dongdong LIN, and Yu-Ping Wang, Classification of multicolor fluorescence in situ hybridization (M-FISH) image using structure based sparse representation model with different constraints, International Symposium on Biomedical Imaging (ISBI 2013), San Francisco, CA, USA, April 8-11, 2013
  23. Dongdong LIN, Jigang Zhang, Jingyao Li, Vince Calhoun, Yu-Ping Wang, Identifying genetic connections with brain functions in schizophrenia using group sparse canonical correlation analysis, International Symposium on Biomedical Imaging (ISBI 2013), San Francisco, CA, USA, April 8-11, 2013
  24. Jinyao Li and Yu-Ping Wang, Classification of Multicolor Fluorescence In-Situ Hybridization (M-FISH) Image Using Regularized Multinomial Logistic Regression, 2012 ACM Conference on Bioinformatics, Computational Biology and Biomedicine (ACM-BCB 2012), Orlando, FL, Oct. 7-10, 2012.
  25. Junbo Duan, Ji-Gang Zhang, Hongbao Cao, Hong-Wen Deng and Yu-Ping Wang. Copy Number Variation Estimation from Multiple Next-generation Sequencing Samples, 2012 ACM Conference on Bioinformatics, Computational Biology and Biomedicine (ACM-BCB 2012), Orlando, FL, Oct. 7-10, 2012.
  26. Jinyao Li, and Yu-Ping Wang, Classification of Multicolor Fluorescence In-Situ Hybridization (M-FISH) Image Using Structure Based Sparse Representation Model, 2011 IEEE International Conference on Bioinformatics and Biomedicine (BIBM12), Philadelphia, PA, Oct. 4-7, 2012.
  27. Hongbao Cao, Vince Calhoun and Yu-Ping Wang, Biomarker Identification for Diagnosis of Schizophrenia with Integrated Analysis of fMRI and SNPs, 2011 IEEE International Conference on Bioinformatics and Biomedicine (BIBM12), Philadelphia, PA, Oct. 4-7, 2012.
  28. Dongdong Lin, Vince Calhoun and Yu-Ping Wang, Correspondence between fMRI and SNP data by canonical correlation analysis, Workshop on Multiscale Biomedical Image Analysis in conjunction with BIBM’12, Philadelphia, PA, Oct. 4-7, 2012.
  29. J. Duan, J. Zhang, H. W. Deng, and Y. P. Wang, "Detection of common copy number variation with application to population clustering from next generation sequencing data," the IEEE Int'l Conf. of the Engineering in Medicine & Biology Soc. (EMBS), San Diego, Aug.28-Sept.1, 2012.
  30. Hongbao Cao, Shufeng Lei, H.W Deng and Yu-Ping Wang, Identification of Genes for Complex Diseases by Integrating Multiple Types of Genomic Data the IEEE Int'l Conf. of the Engineering in Medicine & Biology Soc. (EMBS), San Diego, Aug.28-Sept.1, 2012.
  31. Dongdong Lin, Hongbao Cao, Vince Calhoun, Yu-Ping Wang, Integrating of SNPs and fMRI data for improved classification of schizophrenia, 2011 IEEE International Conference on Bioinformatics and Biomedicine (BIBM11), Atlanta, GA, Nov. 12-15, 2011. A journal version is being submitted.
  32. Wenlong Tang, Hongbao Cao, Jigang Zhang, Junbo Duan and Yu-Ping Wang, Classifying Six Glioma Subtypes from Combined Gene Expression and CNVs Data Based on Compressive Sensing Approach, 2011 IEEE International Conference on Bioinformatics and Biomedicine (BIBM11), Atlanta, GA, Nov. 12-15, 2011.
  33. Junbo Duan, Ji-Gang Zhang, John Lefante, Hong-Wen Deng and Yu-Ping Wang, Detection of copy number variation from next generation sequencing data with total variation penalized least square optimization, 2011 IEEE International Conference on Bioinformatics and Biomedicine (BIBM11), Atlanta, GA, Nov. 12-15, 2011.
  34. Junbo Duan and and Yu-Ping Wang, A joint method to process atomic force microscopy retraction force curves with model selection, Microscopic Image Analysis with Applications in Biology, Chicago, IL, August 1, 2011, MIAAB’11, Aug. 1-3, 2011
  35. Hongbao Cao and Yu-Ping Wang, Classification of multi-color florescence in-situ hybridization (M-FISH) images with sparse representation, ACM Conference on Bioinformatics, Computational Biology and Biomedicine 2011 conference, Chicago, Aug. 1-3, 2011
  36. Yu-Ping Wang, Integrated Analysis of Gene Expression and Gene Copy Number for Gene Shaving based on ICA Approach, 2011 5th International Conference on Bioinformatics and Biomedical Engineering, Wuhan, China, May 10-12, 2011.
  37. Hongbao Cao and Yu-Ping Wang, M-Fish Image Analysis with Improved Adaptive Fuzzy bC-Means Clustering based Segmentation and Sparse Representation Classification,  Proceedings at the ISCA 3rd International Conference on Bioinformatics and Computational Biology (BICoB-2011), March 23-25, 2011 New Orleans, USA
  38. Hongbao Cao and Yu-Ping Wang, Integrated Analysis of Gene Expression and Copy Number Data using Sparse Representation Based Clustering Model, Proceedings at the ISCA 3rd International Conference on Bioinformatics and Computational Biology (BICoB-2011), March 23-25, 2011 New Orleans, USA
  39. Wenlong Tang, Hongbao Cao, and Yu-Ping Wang, Subtyping of Leukemia with Gene Expression Analysis Using Compressive Sensing Method, IEEE Conference on Healthcare Informatics, Imaging and Systems Biology, July 27-29. 2011, San Jose, USA
  40. Wenlong Tang, Uri Tasch, Nagaraj Neerchal, Paul Yarowsky and Yu-Ping Wang, Detection of gait abnormalities in Sprague-Dawley rats after 6-hydroxydopamine injection and the experiment efficient design, IEEE Conference on Healthcare Informatics, Imaging and Systems Biology, July 27-29. 2011, San Jose, USA
  41. Hongbao Cao, and Yu-Ping Wang, Segmentation of M-FISH images for improved classification of chromosomes with an adaptive fuzzy c-means clustering approach, International Symposium on Biomedical Imaging (ISBI 2011), March 29-April 1, 2011, Chicago
  42. Yu-Ping Wang, Qiang Wu and Su-Shing Chen, Multiscale genomic imaging with wavelets signal analysis, International Joint Conference on Bioinformatics, Systems Biology and Intelligent Computing (IJCBS'09), Aug. 3-6, 2009, Shanghai, China.
  43. Su-shing chen, Qingfeng Song and Yu-Ping Wang, Genomic Imaging: A Modern Environment for TCM Research, International Joint Conference on Bioinformatics, Systems Biology and Intelligent Computing (IJCBS'09), Aug. 3-6, 2009, Shanghai, China.
  44. S.-S. Chen and Yu-Ping Wang, Translational Systems Genomics: Ontology and Imaging, First AMIA Summit on Translational Bioinformatics, San Francisco, CA, March 15-17, 2009.
  45. Yu-Ping Wang, Detection of Chromosomal Abnormalities with Multi-color Fluorescence In Situ Hybridization (M-FISH) Imaging and Multi-Spectral Wavelet Analysis, 30th Annual International IEEE EMBS Conference of the IEEE Engineering in Medicine and Biology Society in Vancouver, British Columbia, Canada, August 20-24, 2008.
  46. Yu-Ping Wang, Integration of Gene Expression and Gene Copy Number Variations with Independent Component Analysis, 30th Annual International IEEE EMBS Conference of the IEEE Engineering in Medicine and Biology Society in Vancouver, British Columbia, Canada, August 20-24, 2008.
  47. Yu-Ping Wang, Maheswar Gunampally, Jie Chen Douglas Bittel, Merlin G. Butler and Wei-Wen Cai, Accurate Quantification of Gene Expression using Fuzzy Clustering Approaches, Proceedings of the IEEE International Workshop on Genomic Signal Processing (GENSIPS'07), Gustavelund, Tuusula, Finland, June 10-12, 2007.
  48. Yu-Ping Wang, Classification of Multi-color Fluorescence In Situ Hybridization (M FISH) Images with Multi-Spectral Wavelet Representations, IEEE 7th International Symposium on Bioinformatics & Bioengineering (IEEE BIBE 2007), in Boston, Oct. 14-17.
  49. Yu-Ping Wang, Identification of amplifications and deletions in array CGH data using a differential wavelet analysis, IEEE 7th International Symposium on Bioinformatics & Bioengineering (IEEE BIBE 2007), in Boston, Oct. 14-17.
  50. Fazel A., Derakhshani R., and Wang Y., “Classification of Multicolor Fluorescence In Situ Hybridization Images using Gaussian Mixture Models”, Proceedings of ANNIE 2006 Conference, St. Louis, MO, 2006.
  51. J. Chen and Yu-Ping Wang, Detection of DNA copy number changes using statistical change point analysis, Proceedings of the IEEE International Workshop on Genomic Signal Processing 2006, May, College Station, TX.
  52. Yu-Ping Wang and Ashok Dandpat, Classification of Multi-spectral Florescence in Situ Hybridization Images with Fuzzy Clustering and Multiscale Feature Selection, Proceedings of the IEEE International Workshop on Genomic Signal Processing 2006, May, College Station, TX.
  53. Yu-Ping Wang, Y. Wang and P. Spencer, A differential wavelet-based noise reduction approach to improve the clustering of hyperspectral Raman imaging data, 2006 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, April 6-9, Arlinton, VA, 2006.
  54. Yu-Ping Wang, Maheswar Reddy Gunampally and Wei-Wen Cai, Automated segmentation of microarray spots using fuzzy clustering approaches, 2005 IEEE International Workshop on Machine learning for signal processing, September 28 - 30, Mystic, Connecticut. Special Session on machine learning for genomic signal processing, invited paper.
  55. Yu-Ping Wang, Ragib Husain,, Chi-Ming Huang, Automated recognition of synaptic varicosities from microscope, 2005 IEEE International Workshop on Machine learning for signal processing, September 28 - 30, Mystic, Connecticut.
  56. Yu-Ping Wang, Wavelets meet genetic Imaging, Proceedings of SPIE Vol. #5914, conference on Wavelets XI, San Diego, July 31-Aug3, 2005. Invited keynote talk.
  57. Yu-Ping Wang, Fast Frequency estimation using spline wavelets, Proceedings of SPIE Vol. #5914, conference on Wavelets XI, San Diego, July 31-Aug. 3, 2005.,/
  58. Yu-Ping Wang and Ashok Kumar Dandpat, “Segmentation of chromosome regions from multi-color fluorescence in situ hybridization images by fuzzy clustering approaches”, Proceedings of the IEEE International Workshop on Genomic Signal Processing 2005, May, Newport, RI.
  59. Yu-Ping Wang, A. Dandpat and K. Castleman, Classification of M-FISH Images using Fuzzy C-means Clustering Algorithm and Normalization Approaches, Asilomar Conferences on Signals, Systems and Computers, 7-10, Nov., 2004. Invited paper.
  60. Yu-Ping Wang, M-FISH image registration and classification, 2004 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, April, Arlinton, VA, 2004. invited paper.
    61.  
  61. P. Yanala, T. Lu, F. El-Ghussein, C. Zhao, D. Medhi, Y-P. Wang, J. Knopp, J.H.M. Knoll, and P.K. Rogan, Automated detection of metaphase chromosomes in FISH and routine cytogenetics, 2004 American Society of Human Genetics meeting, Canada, 2004.
  62. Wu, Q., T. Chen, X. Li, Y. Wang and K.R. Castleman, "A Multiresolution Autofocusing Method for Automated Microscopy", Microscopy & Microanalysis, San Antonio, TX, Aug. 2003.
  63. Yu-Ping Wang, Q. Wu, K. Castleman, and Z. Liu, Fast filter bank implementation of image interpolation at any scales, 2002 International Conference on Acoustics, Speech and Signal Processing, Orlando, FL, May 13-17, 2002
  64. Wu, Q., Z. Liu, Z. Xiong, Y. Wang, T. Chen and K. R. Castleman, "On optimal subspaces for appearance-based object recognition", 2002 International Conference on Image Processing , Rochester, NY, USA, 2002.
  65. Wu, Q., Y. Wang,, Z. Liu, T. Chen and K. R. Castleman, "The effect of image enhancement on biomedical pattern recognition", Second Joint IEEE EMBS-BMES Conference, Houston, Oct. 23-26, TX, 2002.
  66. Yu-Ping Wang, Q. Wu, K. Castleman, and Z. Xiong, Image enhancemnent using multiscale differential operators, 2001 International Conference on Acoustics, Speech and Signal Processing, Salt Lake City, UT, May, 2001.
  67. Z. Liu, Q. Wu, Z. Xiong, Y. Wang, and K. Castleman, Cascaded differential and wavelet compression of chromosome images, to appear in Proc. SPIE Symposium on Optical Science and Technology, San Diego, CA, August 2001.
  68. Yu-Ping Wang, A. A. Amini, Fast techniques for determining Myocardial Strains from Tagged MRI, World Congress on Medical Physics and Biomedical Engineering, June 2000, Chicago IL.
  69. Yu-ping Wang, S. L. Lee, A general framework for multiscale image representations using B-splines, invited paper, 2000 European Signal Processing Conference.
  70. Wu Qiang, Xiong Zixiang, Ken Castelman, Yu-Ping Wang, Wavelet Based Lossless Coding of Cytogenetic Images with Arbitrary Regions of Support, 2000 IEEE International symposium on Intelligent Signal Processing and Communication Systems. Honolulu, HI, November 2000.
  71. Yu-ping Wang, Multiscale Image Representations from B-splines, Lecture notes. A talk based on this has been given at Washington University, Univ. of Penn., Texas A&M, 2000.
  72. Yu-Ping Wang, Q. Wu, K. Castleman, and Z. Xiong, Image enhancement using multiscale oriented wavelets, 2001 International Conference on Image Processing, Thessaloniki, Greece, October 7-10, 2001.
  73. Peng-Ling He, Yu-Ping Wang and Yi-Jun Liang, "B-Spline Contour Fitting and Transform Representation for Computer Vision," Europe-China Workshop On Geometric Modeling and Invariants for Computer Vision, Xi'an, China, April 1995.
  74. Yu-Ping Wang and Yuan-Long Cai, "Construction and Properties of B-Spline Wavelet Filters for Multiscale Edge Detection," in Proc.IEEE International Conference on Image Processing, Washington, D.C., U.S.A., October 1995.
  75. Yu-Ping Wang, "The Construction and Properties of Wavelet Packet Bases," Proceedings of International Conference on Neural Network and Signal Processing, Guangzhou, China, 1993.
  76. Yu-Ping Wang and Gui-Zhong Liu, "Application of Wavelet Transform to the Time-Varying Filtering of Seismic Signals," Presented at the Western Oil Exploration Conference in China, September 1993.
  77. Yu-Ping Wang and Gui-Zhong Liu, "Reconstruction of Images from Its Projections by Wavelet Transform," Proc. of 4th National CTConference, Beijing, China, October 1992.
  78. Yu-Ping Wang and Yuan-Long Cai, Peng-Ling He, "A Family of Multiscale B-Spline Wavelet Transforms," in Proceedings of International Conference on Neural Network and Signal Processing, Nanjing, China, 1995.
  79. Gui-Zhong Liu, Shuang-Liang Di and Yu-Ping Wang, "Nonorthogonal Wavelet Packet Transform," National Conference on Neural Network, Xi'an, China, October 1993.
  80. Yu-Ping Wang, and Sheng-Wang Zhu, "Filtering the Random Seismic Noise Using Multiscale B-spline wavelet," Technical reports.
  81. Yu-Ping Wang, "Wavelet Theory and its Potential Application to 3-D Computer Vision," Procedings of Mathematical Research in Celebrating 100th anniversary of Tianjin University (Peiyang University), Oct., 1995.
  82. Yu-Ping Wang, Yuan-long Cai, "Multiscale B-Spline Theory and its Application to Computer Vision," Technical reports, 1996.
  83. Yu-Ping Wang, and S. L. Lee, From Gaussian Scale-space to B-spline Scale-space, 1999 International Conference on Acoustics, Speech and Signal Processing, Phonix, AZ, May 2001.
  84. Yu-Ping Wang, A family of multi-orientation wavelet transforms and the comparison with the Radon transform, Technical report, Dec., 1997.
  85. Yu-Ping Wang, A. A. Amini, Fast computation of tagged MRI motion fields with subspace approximation techniques, IEEE workshop on Mathematical Methods in Biomedical Image Analysis 2000
  86. J. Chen and Y.P. Wang, Identification of DNA Copy Number Changes in aCGH Data, Proceedings of The 4th Sino-International Symposium on Probability, Statistics, and Quantitative Management, Taipei, Taiwan, ROC, May 12, 2007

Book Chapters

  1. Yasheng Chen, Yu-Ping Wang and A. A. Amini, "Tagged MRI Image Analysis from Splines", chapter 8, Measurement of Cardiac Deformation from MRI: Physical and Mathematical Models, eds. A.A Amini and J.L. Prince, Kluwer Academic Publishers, 2001.
  2. Yu-Ping Wang, Chapter 5 in Wavelet Theory and Its Applications, Xidian University Press, China, 1993.
  3. Chris Wyat, Yu-Ping Wang, Merray Loew, and Yue Wang, Medical Imaging enhancement, invited book chapter 7, Biomedical Information Technology, in Elsevier-Academic Press Series in Biomedical Engineering, 2007.
  4. Yu-Ping Wang, Qiang Wu, and Ken Castleman, Microscopic image enhancement, invited Book Chapter of Microscopic Image Analysis, edited by Qiang Wu, Fatima Merchant and Ken Castleman, in Elsevier-Academic Press, 2007.
  5. Dongdong Lin, Vince D. Calhoun, and Yu-Ping Wang, Chapter 16. Imaging genetics: information fusion and association techniques between biomedical images and genetic factors, "Health Informatics Data Analysis: Methods and Examples", the Springer book series Health Information Science, edited by Prof. Yanchun Zhang, Victoria University, Australia, 2014.