Journal publications

  1. 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
  2. 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
  3. 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
  4. 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
  5. 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: PMID: 30336254
  6. 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
  7. 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]
  8. 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
  9. 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
  10. 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
  11. 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,
  12. 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:
  13. 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
  14. 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.
  15. 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
  16. 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]
  17. 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
  18. 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
  19. 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]
  20. 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]
  21. 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
  22. 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
  23. 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]
  24. 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
  25. 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
  26. 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:, PMID: 27867012, PMCID: PMC5237618
  27. 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
  28. 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]
  29. 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]
  30. 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]
  31. 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
  32. 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]
  33. 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]
  34. 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]
  35. 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]
  36. 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]
  37. 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]
  38. 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]
  39. 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]
  40. 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]
  41. 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]
  42. 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]
  43. 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]
  44. 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]
  45. 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]
  46. 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]
  47. 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]
  48. 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]
  49. 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]
  50. 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]
  51. 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]
  52. 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]
  53. 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]
  54. 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]
  55. 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]
  56. 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]
  57. 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]
  58. 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
  59. 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/ IF=4.087 [PDF file]
  60. 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]
  61. 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]
  62. 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]
  63. 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]
  64. 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]
  65. 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]
  66. 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]
  67. 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]
  68. 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]
  69. 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]
  70. 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]
  71. 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]
  72. 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]
  73. 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]
  74. 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]
  75. 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]
  76. 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]
  77. 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]
  78. 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]
  79. 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]
  80. 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]
  81. 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]
  82. 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]
  83. 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]
  84. 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]
  85. Yu-Ping Wang and Wei-Wen Cai, Genetic imaging: where imaging science meets cytogenetic research, Biophotonics Magazine, Nov., 2004.
  86. 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]
  87. 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]
  88. 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]
  89. 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]
  90. 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]
  91. 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]
  92. 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]
  93. 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]
  94. 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]
  95. 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.
  96. 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.
  97. 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.
  98. 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.
  99. 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.
  100. 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.
  101. Yu-Ping Wang and Yuan-Long Cai, A Type of B-Spline Wavelet and the Associated Fast Algorithms, to appear at Signal Processing(Chinese).
  102. 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.
  103. Yu-Ping Wang, A Wavelet is Creating Great Waves, Science (Chinese), vol.47, no.4, 1995.
  104. 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.
  105. 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.
  106. 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.
  107. Yu-Ping Wang and Yuan-Long Cai, Filtering Based on Wavelet Transform, Information and Control, 1996.