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.

Journal publications

  1. 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, DOI: 10.1109/TMI.2017.2721301
  2. 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, 29 June 2017, DOI: 10.1109/TMI.2017.2721640
  3. 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, 2017,DOI: 10.1109/TBME.2017.2771483
  4. 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, accepted, 2017
  5. 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. Epub 2017 Oct 10.
  6. 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)
  7. 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, 2017, May 17. doi: 10.1093/schbul/sbx068
  8. 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; PubMed Central PMCID: PMC5461698.
  9. 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
  10. Keith Dillon, Vince Calhoun, and Y.-P. Wang, A Robust Sparse-Modeling Framework for Estimating Schizophrenia Biomarkers from fMRI. Journal of Neuroscience Methods, Volume 276, 30 January 2017, Pages 46–55. DOI:http://dx.doi.org/10.1016/j.jneumeth.2016.11.005
  11. 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, in press, 2017.
  12. 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). First published online: July 27, 2016. doi: 10.1093/bioinformatics/btw485 [PDF file]
  13. 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, September 2016. Volume: PP, Issue: 99. DOI: 10.1109/TCBB.2016.2607717 [PDF file]
  14. 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]
  15. 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
  16. 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; 17: 247. Published online: Jun 21 2016. doi: 10.1186/s12859-016-1122-6 [PDF file]
  17. 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, Bioinformatics (2015). First published online: October 12, 2015.(2016) 32 (3): 330-337. doi: 10.1093/bioinformatics/btv586 [PDF file]
  18. M. Wang, T.Z. Huang, J. Li and Yu-Ping Wang, A Patch-Based Tensor Decomposition Algorithm for M-FISH Image Classification, Cytometry, Part A. First published: April 2016. doi: 10.1002/cyto.a.22864 [PDF file]
  19. Keith Dillon and Y.-P. Wang, Imposing Uniqueness to Achieve Sparsity, Signal Processing.Vol. 123, June 2016, pp. 1-8. doi: 10.1016/j.sigpro.2015.12.009 [PDF file]
  20. 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 [PDF file]
  21. 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. Published online: Mar 2 2016. vol. PP, no.99, pp.1-1 doi: 10.1109/TVCG.2016.2537341 [PDF file]
  22. 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, Published: January 25, 2016.(11)(1): e0147475 doi:10.1371/journal.pone.0147475 [PDF file]
  23. 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. Volume 581, Issue 2, May 2016, pp.152-160. pii: S0378-1119(16)00098-6. doi: 10.1016/j.gene.2016.01.036. [PDF file]
  24. 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 [PDF file]
  25. 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 [PDF file]
  26. 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. [PDF file]
  27. 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]
  28. 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. Epub 2014 Sep 9. [PDF file]
  29. 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. [PDF file]
  30. 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, 27 October 2014. doi: 10.3389/fcell.2014.00062. [PDF file]
  31. 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. Epub 2014 Sep 4. [PDF file]
  32. 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 (JBCB) Vol. 12, issue 4, 2014. doi: 10.1142/S0219720014500218 [PDF file]
  33. 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. Epub 2014 Aug 13. [PDF file]
  34. 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 First published online: July 24, 2014. [PDF file]
  35. 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, doi: 10.1109/TVCG.2014.2312015. First published online: 14 March 2014. [PDF file]
  36. 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. Epub 2014 Feb 12. [PDF file]
  37. J. Duan, H. W. Deng, and Y. P. Wang, Common copy number variation detection from multiple sequenced samples, IEEE Trans. Biomedical Engineering, Vol.61, No.3, March 2014. doi: 10.1109/TBME.2013.2292588, Date of publications: Nov.26, 2013. [PDF file]
  38. 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. Epub 2013 Nov 17. IF=7.692 [PDF file]
  39. 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. Epub 2013 Oct 11. IF=5.047 [PDF file]
  40. 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]
  41. 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]
  42. 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
  43. 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]
  44. 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]
  45. 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]
  46. 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]
  47. 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]
  48. 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]
  49. 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]
  50. 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]
  51. 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]
  52. 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]
  53. 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]
  54. 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]
  55. 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]
  56. 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]
  57. 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]
  58. 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]
  59. 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]
  60. 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]
  61. 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]
  62. 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]
  63. 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]
  64. 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]
  65. 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]
  66. 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]
  67. 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]
  68. 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]
  69. Yu-Ping Wang and Wei-Wen Cai, Genetic imaging: where imaging science meets cytogenetic research, Biophotonics Magazine, Nov., 2004.
  70. 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]
  71. 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]
  72. 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]
  73. 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]
  74. 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]
  75. 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]
  76. 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]
  77. 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]
  78. 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]
  79. 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.
  80. 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.
  81. 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.
  82. 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.
  83. 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.
  84. 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.
  85. Yu-Ping Wang and Yuan-Long Cai, A Type of B-Spline Wavelet and the Associated Fast Algorithms, to appear at Signal Processing(Chinese).
  86. 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.
  87. Yu-Ping Wang, A Wavelet is Creating Great Waves, Science (Chinese), vol.47, no.4, 1995.
  88. 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.
  89. 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.
  90. 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.
  91. 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.  
  62. 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.
  63. 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.
  64. 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
  65. 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.
  66. 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.
  67. 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.
  68. 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.
  69. 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.
  70. Yu-ping Wang, S. L. Lee, A general framework for multiscale image representations using B-splines, invited paper, 2000 European Signal Processing Conference.
  71. 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.
  72. 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.
  73. 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.
  74. 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.
  75. 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.
  76. Yu-Ping Wang, "The Construction and Properties of Wavelet Packet Bases," Proceedings of International Conference on Neural Network and Signal Processing, Guangzhou, China, 1993.
  77. 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.
  78. 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.
  79. 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.
  80. Gui-Zhong Liu, Shuang-Liang Di and Yu-Ping Wang, "Nonorthogonal Wavelet Packet Transform," National Conference on Neural Network, Xi'an, China, October 1993.
  81. Yu-Ping Wang, and Sheng-Wang Zhu, "Filtering the Random Seismic Noise Using Multiscale B-spline wavelet," Technical reports.
  82. 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.
  83. Yu-Ping Wang, Yuan-long Cai, "Multiscale B-Spline Theory and its Application to Computer Vision," Technical reports, 1996.
  84. 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.
  85. Yu-Ping Wang, A family of multi-orientation wavelet transforms and the comparison with the Radon transform, Technical report, Dec., 1997.
  86. 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
  87. 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