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Biomedical Computing and Intelligent Systems Lab

The Biomedical Computing and Intelligent Systems Lab focuses on developing efficient algorithms to solve computational problems in basic medicine and clinics, while making theoretical and fundamental contributions to statistical pattern recognition, machine learning, and computer vision.

Specifically, the lab is working on topics such as: 

  • Computational biology and bioinformatics (gene expression/protein expression microarray analysis, mass spectrometry for proteomics, signaling pathways, system biology, high-throughput data analysis)
  • Molecular/cellular image processing
  • Pattern recognition and computer vision
  • Statistical machine learning, data mining

Personnel

  • Jean Gao, Ph.D., Director
  • Dongsung Kim, Ph.D., Visiting Scholar

Collaborators

  • Gary Arbique, UTSW (Radiology)
  • Spencer Brown, UTSW (Plastic Surgery)
  • Youngjoong Joo, Arizona State University (Electrical Engineering)
  • Sungyong Jung, UTA (Electrical Engineering)
  • Kate Luby-Phelps, UTSW (Cell Biology)
  • Kevin Rosenblatt, UTSW (Pathology)
  • Michael Saint-Cyr, UTSW (Radiology)
  • John Schorge, UTSW (Ob-Gyn)
  • Liping Tang, UTA (Bioengineering)
  • Yingming Zhou, UTSW (Biochemistry)

Current Graduate Students

  • Borzou Alipourard (Ph.D.)
  • Ashis Kumer Biswas (Ph.D.)
  • Jumi Cho (Undergraduate)
  • Piraporn Jangyodsuk (Ph.D.)
  • Fariba Khoshghalbvash (Ph.D.)
  • Nhat C. Tran (Ph.D.)

Alumni

  • Pinaki Bose, B.S.
  • Mingon Kang, Ph.D. (Asst. Professor, Texas A&M Commerce)
  • Dongchul Kim, Ph.D. (Asst. Professor, UT Rio Grande Valley)
  • Young Bun Kim, Ph.D. (Research associate, UT Southwestern Medical Center)
  • Shuo Li, Ph.D. (Symantec)
  • Minh Nguyen
  • Jung Hun Oh, Ph.D. (Research associate, Washington University in Saint Louis)
  • Rachit Kumar Shah
  • Akihiro Takei, B.A.
  • Ninad Thakoor, Ph.D. (Post-doc, UC Riverside)
  • Quan Wen, Ph.D. (Lawrence Berkeley National Lab)
  • Ravi Yadav, M.S.

Funding

  • National Science Foundation
  • National Institutes of Health
  • American Cancer Society

Current Research

  • Intracellular Cell Dynamics Analysis System: 

    New discoveries in biology have required an extensive knowledge of cell dynamics. Knowledge of subcellular particles/structures such as organelles vesicles, and mRNAs is critical to understand how cells regulate delivery of specific proteins from the site of synthesis to the site of action for a better understanding of diseases and viral infections. Quantitative spatial-temporal protein mobility study plays an essential role in experimentally comprehending and validating protein signaling mechanisms and protein-protein interactions. The goal of this system is to develop a unique and the first web-based open access Intracellular Cell Dynamics Analysis System (ICellDAS) for automating subcellular particle motion estimation, tracking and mobility analysis.

  • Proteomics Biomarker Information System:

    We have used high resolution mass spectrometry (MS), MALDI-TOF (matrix-assisted laser desorption/ionization time-of-flight) and SELDI-TOF (surface-enhanced laser desorptin/ionization time-of-flight), to study serum proteomic profiling. To analyze the complex mass spectra whose number of mass-to-charge data points (a.k.a. features in pattern recognition) easily goes beyond one million, sophisticated bioinformatics algorithms have to be explored to robustly discover and identify these unique proteomic patterns.

  • Marker Gene Selection and Clustering:

    PFSBEM (hybrid PCA based Feature Selection and Boost- Expectation-Maximization clustering) is for unsupervised gene selection. It uses a two step approach to select marker genes. The first step retrieves feature subsets with original physical meaning based on their capacities to reproduce sample projections on PCs. The second step then searches for the best feature subsets that maximize clustering performance. To improve the quality of partitioning, we explored cluster ensemble approaches based on boosting and cluster validity index.

  • Protein/Peptide Identification by Tandem Mass Spectrometry:

    To find the cause or consequence of pathology, a two-way parallel searching for de novo peptide identification has been developed to greatly reduce the number of candidate sequences. By utilizing properties of b- and y- ions, our algorithm filters out peptide candidates. A mass-to-charge intensity based criterion is then developed for further pruning.

  • Minimum Error Shape Classifier:

    We have developed a weighted hidden-Markov model (HMM) classifier using generalized probabilistic descent method (GPD) for minimum error recognition. Different from traditional Maximum Likelihood (ML) methods, in which classification is based on probabilities from independent individual class models as is the case for general HMM methods, our method utilizes information from all classes to minimize classification error. We have tested different datasets by using our approach and classic ML classification with various HMM topologies alongside Fourier descriptor and Zernike moments based Support Vector Machine (SVM) classification.

Selected Publications

Journal Articles & Book Chapters

  • M. Kang, J. Park, D. Kim, A. Biswas, C. Liu and J. Gao, "Multi-Block Bipartite Graph for Multimodal Genomic Data," IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), (impact factor 1.609), Accepted on June 14, 2016.
  • M. Kang, L. Tang, and J. Gao, "Computational modeling of phagocyte transmigration for foreign body responses to subcutaneous biomaterial implants in mice," BMC Bioinformatics, (impact factor 2.576), Accepted on Feb 15, 2016.
  • S. Hill, L. Heiser, D. Kim, M. Kang, J. Gao, etc, "Inferring causal molecular networks: empirical assessment through a community-based effort," Nature Methods, (impact factor: 32.072), Accepted on Jan 28, 2016.
  • A. Biswas, M. Kang, D. Kim, C. Ding, B. Zhang, X. Wu and J. Gao, "Inferring disease associations of the long non-coding RNAs through non-negative matrix factorization," Network Modeling Analysis in Health Informatics and Bioinformatics (NetMAHIB), Vol. 4, No. 1, pp. 1-17, 2015.
  • S. Li, J. Nyagilo, D. Dave, W. Wang, B. Zhang, and J. Gao, "Probabilistic partial least squares regression for quantitative analysis of Raman spectra," International Journal of Data Mining & Bioinformatics, Vol. 11, No. 2, pp. 223-243, 2015.
  • M. Kang, C. Zhang, H. Chun, C. Ding, C. Liu and J. Gao, "eQTL epistasis: detecting epistatic effects and inferring hierarchical relationships of genes in biological pathway," Bioinformatics, (current 5 year impact facto: 6.968) doi: 10.1093/bioinformatics/btu727, 2014.
  • D. Kim, J. Wang, C. Liu, and J. Gao, "Inference of SNP-Gene Regulatory Networks by Integrating Gene Expressions and Genetic Perturbations," BioMed Research International (SCI impact factor 2.88), vol. 2014, Article ID 629697, 9 pages, doi:10.1155/2014/629697, 2014.
  • A. Biswas, B. Zhang, X. Wu and J. Gao, "CNCTDiscriminator: Coding and Non-coding Transcript Discriminator-An Excursion through Hypothesis Learning and Ensemble Learning Approaches," Journal of Bioinformatics and Computational Biology, vol. 11, no. 5, id 1342002, 2013.
  • S. Li, J. Nyagilo, D. Dave, and J. Gao, "Models and Methods for Quantitative Analysis of Raman Spectra," IEEE Journal of Biomedical and Health Informatics, vol. 18, no. 2, pp. 525-536, 2014.
  • S. Li, J.O. Nyagilo, D.P. Dave and J. Gao, "Continuous Wavelet Transform based PLS Regression method for Quantitative Analysis of Raman Spectra", IEEE Transactions on Nanobioscience, vol. 12, no. 3, pp. 214-221, 2013
  • S. Li, J. Nyagilo, D. Dave, B. Zhang, and J. Gao, "Eigenspectra, a robust regression method for multiplexed surface enhanced Raman spectra analysis," International Journal of Data Mining & Bioinformatics, vol. 7, no. 4, pp. 358-75, 2012.
  • D. Kim, X. Wang, C. Yang, and J. Gao, "A Framework for Personalized Medicine with Reverse Phase Protein Array and Drug Sensitivity," Proteome Science (impact factor: 2.49), 10(Suppl 1):S13, 2012
  • J.H. Oh and J. Gao, "Fast kernel discriminant analysis for classification of liver cancer mass spectra," IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 8, no. 6, pp. 1522-1534, 2011.
  • N. Thakoor and J. Gao, "Branch-and-bound for model selection and its computational complexity," IEEE Transactions on Knowledge and Data Engineering, vol. 23, no. 5, pp. 655-668, 2011.
  • D. Kim, X. Wang, C. Yang, and J. Gao, "Learning biological network using mutual information and conditional independence," BMC Bioinformatics, 11(Suppl 3):S9, 2010.
  • N. Thakoor, J. Gao, and V. Devragen, "Multibody structure-and-motion segmentation by branch-and-bound model selection," IEEE Transactions on Image Processing, Volume 19 Issue 6, June 2010.
  • J.H. Oh and J. Gao, "A kernel-based approach for detecting outliers of high-dimensional biological data," BMC Bioinformatics (impact factor: 3.49), 10(Suppl 4): S7, April 2009.
  • J. Oh, P. Gurnani, L. Knowles, J. Schorge, K. Rosenblatt, and J. Gao, "An extended Markov blanket approach to proteomic biomarker detection from high-resolution mass spectrometry data," IEEE Transactions on Information Technology in Biomedicine, vol. 13, Issue 2, pp. 195-206, March 2009.
  • J. Oh, Y. Kim, P. Gurnani, K. Rosenblatt, and J. Gao, "Biomarker selection and sample prediction in multi-category disease on MALDI-TOF data," Bioinformatics, (impact factor: 4.894), vol. 24, no. 16, pp. 1812-1818, 2008.
  • N. Thakoor, J. Gao, and V. Devarajan, "Multi-stage branch-and-bound merging for planar surface segmentation in disparity Space," IEEE Transactions on Image Processing, vol. 17, Issue 11, pp. 2217-2226, Nov. 2008.
  • Q. Wen, K. Luby-Phelps, and J. Gao, "Tracking multiple subcellular structures using a sequential Monte Carlo approach," International Journal of Data Mining & Bioinformatics, vol. 3, no. 3, 2009.
  • S. Pan, J. Rush, E. R. Peskind, D. Galasko, K. Chung, J. Quinn, J. Jankovic, J. B. Leverenz, C. Zabetian, C. Pan, Y. Wang, J. Oh, J. Gao, J. Zhang, T. Montine and J. Zhang, "Application of targeted quantitative proteomics analysis in human cerebrospinal fluid using an LC MALDI TOF/TOF platform," Journal of Proteome Research, (impact factor: 5.151), vol. 7, Issue 2, pp. 720-730, Feb. 2008.
  • S. Gopinath, Q. Wen, N. Thakoor, K. Luby-Phelps, J. Gao, "A statistical approach for intensity loss compensation of confocal microscopy images," Journal of Microscopy (Blackwell publishing), vol. 230, pp. 143-159, 2008.
  • N. Thakoor, J. Gao and S. Jung, "Hidden Markov model based weighted likelihood discriminant for 2D shape classification," IEEE Transactions on Image Processing, vol. 16, Issue 11, pp. 2707 - 2719, Nov. 2007.
  • J. Xue, G. Arbique, D. Hatef, S. Brown, M. Saint-Cyr, J. Gao, "Four-dimensional vascular tree reconstruction using moving grid deformation,"  Academic Radiology, vol. 14, Issue 12, pp. 1540-1553, Dec. 2007.
  • H. Shu, Q. Liang, and J. Gao, "Wireless sensor network lifetime analysis using interval type-2 fuzzy logic systems," IEEE Transactions on Fuzzy Systems, vol. 16, no. 2, pp. 416-427, 2008.
  • P. Machalak, Y. Kim, and J. Gao, "Computational challenges of microarray analysis," in Computational Genomics: Current Methods, Horizon Scientific Press, Hethersett, UK, 2007.
  • J. Oh, A. Nandi, P. Gurnani, L. Knowles, and J. Schorge, K. Rosenblatt, and J. Gao, "Identifying biomarkers to predict early relapse in ovarian cancer," Journal of Bioinformatics and Computational Biology (JBCB), vol.4, no.6, 2006. 
  • J. Gao, "New discoveries of image display size on observer performance," Academic Radiology (Elsevier), vol.13, no.4, pp.407-408, 2006.
  • J. Oh and J. Gao, "A two-way parallel searching for peptide identification via tandem mass spectrometry," Special Issue on Bioinformatics, Engineering Letters, (invited paper) accepted in June 2006.
  • J. Gao, A. Kosaka, and A. Kak, "A multi-Kalman filtering approach for video tracking of human-delineated objects in cluttered environments," Computer Vision and Image Understanding, vol. 99, no. 1, pp. 1-57, 2005.
  • K. Nojima, S. Brown, C. Acikel, J. Janis, G, Arbique, T. Abulezz, J. Gao, Q. Wen, K. Kurihara, R. Rohrich, "Defining vascular supply and territory of thinned perforator flaps: Part II. superior gluteal artery perforator flap," Plastic and Reconstructive Surgery, vol. 118, no. 6, pp. 1338-1348, 2006.
  • J. Oh, J. Gao, A. Nandi, P. Gurnani, L. Knowles, J. Schorge, and K. Rosenblatt, "Diagnosis of early relapse in ovarian cancer using serum proteomic profiling," Genome Informatics, vol.16, no. 2, pp.195-204, 2005.
  • N. Thakoor and J. Gao, "Occlusion resistant shape classifier based on warped optimal path matching," International Transactions on Communication and Signal Processing, vol. 9, no. 1, 2006.
  • J. Gao, A. Kosaka, and A. Kak, "A deformable model for human CT liver extraction," Academic Radiology (Elsevier), vol. 12, no.9, pp. 1178-1189, 2005
  • J. Gao and L. Waite, "Patellofemoral joint study via image processing," Biomedical Sciences Instrumentation, pp. 151-160, vol. 32, 1996.

Conference Publications:

  • D. Kim, M. Kang, A. Biswas, C. Liu, and J. Gao, "Integrative approach for inference of gene regulatory networks using lasso-based random featuring and application to Psychiatric disorders," Proceedings of IEEE International Conference on Bioinformatics & Biomedicine (IEEE BIBM 2015)(regular paper acceptance rate 19%, 68/346), Washington D.C., USA, Nov. 9-12, 2015.
  • M. Kang, J. Park, D. Kim, A. Biswas, C. Liu, and J. Gao, "An Integrative Genomic Study for Multimodal Genomic Data Using Multi-Block Bipartite Graph," Proceedings of IEEE International Conference on Bioinformatics & Biomedicine (IEEE BIBM 2015)(regular paper acceptance rate 19%, 68/346), Washington D.C., USA, Nov. 9-12, 2015.
  • D. Kim, M. Kang, C. Liu, and J. Gao, "Integration of DNA Methylation, Copy Number Variation, and Gene Expression for Gene Regulatory Network Inference and Application to Psychiatric Disorders," Proceedings of IEEE 14th International Conference on BioInformatics and BioEngineering (IEEE BIBE 2014), Boca Raton, USA, Nov. 10-12, 2014.
  • M. Kang, D. Kim, C. Liu, and J. Gao, "Multi-Block and Multi-Task Learning for Integrative Genomic Study," Proceedings of IEEE 14th International Conference on BioInformatics and BioEngineering (IEEE BIBE 2014), Boca Raton, USA, Nov. 10-12, 2014.
  • A. Biswas, J. Gao, B. Zhang and X. Wu, "NMF-based LncRNA-Disease Association Inference and Bi-clustering," Proceedings of IEEE 14th International Conference on BioInformatics and BioEngineering (IEEE BIBE 2014), Boca Raton, USA, Nov. 10-12, 2014. (Received the best paper award in the Bioinformatics category)
  • M. Kang, S. Li, C. Liu, and J. Gao, "eQTL Epistasis: Detecting Complex Interaction Effects between Multiple Loci from eQTL Data," IEEE International Conference on Bioinformatics & Biomedicine (IEEE BIBM) (regular paper acceptance rate 19.6%), Shanghai, China, Dec. 18-21, 2013.
  • D. Kim, C. Liu, and J. Gao, "Inference of gene regulatory networks by integrating gene expression and genetic perturbations," IEEE International Conference on Bioinformatics and Biomedicine 2013 (IEEE BIBM) (regular paper acceptance rate 19.6%), Shanghai, China, Dec 18-21, 2013.
  • A. Biswas, B. Zhang, X. Wu and J. Gao, "QLZCClust: Quaternary Lempel-Ziv Complexity based Clustering of the RNA-seq Read Block Segments," The 13th IEEE International Conference on Bioinformatics and Bioengineering (IEEE BIBE 2013), Chania, Greece, 10-13 November 2013.
  • M. Kang, S. Li, D. Kim, C. Liu, and J. Gao, "eQTL Mapping Study via Regularized Sparse Canonical Correlation Analysis," IEEE International Conference on Machine Learning and Applications (IEEE ICMLA) (regular paper acceptance rate 27%), Miami, FL, Dec. 4-7, 2013.
  • S. Li, J. Gao, J.O. Nyagilo and D.P. Dave, "Probabilistic Partial Least Square Regression: A Robust Model for Quantitative Analysis of Raman Spectroscopy Data," IEEE International Conference on Bioinformatics & Biomedicine (IEEE BIBM) (regular paper acceptance rate 19.4%), Atlanta, GA, Nov 12-15, 2011.
  • D. Kim, X. Wang, C. Yang, and J. Gao, "A Framework for Personalized Medicine with Reverse Phase Protein Array and Drug Sensitivity and Drug Sensitivity," IEEE International Conference on Bioinformatics & Biomedicine (IEEE BIBM), (19.7 % short paper acceptance rate), Atlanta, GA, Nov 12-15, 2011.
  • S. Li, K. Luby-Phelps, B. Zhang, X. Wu, and J. Gao, "Subcellular Particles Tracking in Time-lapse Confocal Microscopy Images," Proceedings of IEEE Engineering in Medicine and Biology Society (IEEE EMBC), Boston, MA, Aug 30-Sept 3, 2011.
  • D. Kim, C. Yang, X. Wang, B. Zhang, X. Wu, and J. Gao, "Discovery of Lung Cancer Pathways using Reverse Phase Protein Microarray and Prior-Knowledge based Bayesian Networks," Proceedings of IEEE Engineering in Medicine and Biology Society (IEEE EMBC), Boston, MA, Aug 30-Sept 3, 2011.
  • M. Kang, J. Gao, and L. Tang, "Nonlinear RANSAC Optimization for Parameter Estimation with Applications to Phagocyte Transmigration," Proceedings of IEEE International Conference on Machine Larning and Applications (IEEE ICMLA), Honolulu, HI, Dec 18-21 2011.
  • M. Kang, J. Gao, L. Tang, "Computational modeling of phagocyte transmigration during biomaterial-mediated foreign body responses," IEEE International Conference on Bioinformatics & Biomedicine (IEEE BIBM), pp. 609-612, Hong Kong, Dec 18-21, 2010.
  • S. Li, J. Gao, J.O. Nyagilo and D.P. Dave, "Eigenspectra, A Robust Regression Method For Multiplexed Raman Spectra Analysis", IEEE International Conference on Bioinformatics & Biomedicine (IEEE BIBM) (regular paper acceptance rate 17.2%), pp. 525-530, , Hong Kong, Dec 18-21,2010.
  • D. Kim, J. Gao, C. Yang, "Learning Proteomic Network Structure by a New Hill Climbing Algorithm" Proceedings of IEEE Symposium of Bioinformatics and Bioengineering (IEEE BIBE), pp. 191-196, Philadelphia, PA, May 31-Jun 3, 2010.
  • H. Iwaki, A. Kosaka, S. Li, J. Gao, "Motion detection for subcellular structure trafficking," Proceedings of IEEE Engineering in Medicine and Biology Society (IEEE EMBC), pp. 6722-6725, Minneapolis, MN, Sept 2-6, 2009.
  • N. Thakoor and J. Gao, "Branch-and-bound hypothesis selection for two-view multiple structure and motion segmentation," Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition (IEEE CVPR), Anchorage, AK, June 23-28, 2008.
  • Q. Wen and J. Gao, "Tracking interacting subcellular structures by sequential Monte Carlo method," Proceedings of IEEE Engineering in Medicine and Biology Society (IEEE EMBC), pp. 4185-4188, Lyon, France, Aug 22-26, 2007.
  • J. Xue, J. Gao, and L. Tang, "Phagocyte transmigration modeling using system dynamic controls," Proceedings of IEEE Symposium of Bioinformatics and Bioengineering (IEEE BIBE)(full paper acceptance rate < 12%, 60/500+), pp. 480-485, Boston, MA, Oct 14-17, 2007
  • J. Oh, Y. Kim, P. Gurnani, K. Rosenblatt, and J. Gao, "Biomarker selection for predicting Alzheimer disease using high-resolution MALDI-TOF data," Proceedings of IEEE Symposium of Bioinformatics and Bioengineering (IEEE BIBE) (full paper acceptance rate < 12%, 60/500+), pp. 464-471, Boston, MA, Oct 14-17, 2007.
  • J. Xue, J. Gao, G. Arbique, S. Brown, and M. Cyr-Saint, "Three dimensional analysis of the vascular perfusion for anterolateral thigh perforator flaps," Proc. of SPIE Medical Imaging, San Jose, CA, Feb 11-16, 2007.
  • Y. Kim and J. Gao, "Unsupervised gene selection for high dimensional data," Proceedings of IEEE Symposium of Bioinformatics and Bioengineering (IEEE BIBE) (38.8% regular paper acceptance rate), pp. 227-232, Washington DC, Oct 16-18, 2006.
  • Q. Wen, J. Gao, and K. Luby-Phelps, "Markov chain Monte Carlo data association for protein clusters tracking," Proceedings of IEEE International Conference on Pattern Recognition (IEEE ICPR), (15% oral acceptance rate), vol. 1, pp. 1030-1033, Hong Kong, Aug. 20-24, 2006.
  • J. Oh, A. Nandi, P. Gurnani, L. Knowles, J. Schorge, K. Rosenblatt, and J. Gao, "A hybrid feature selection for MALDI-TOF mass spectrometry data analysis," Proceedings of IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (IEEE CIBCB), pp. 36-43, Toronto, Canada, Sept 28-29, 2006.
  • N. Thakoor, J. Gao, Q. Wen, and S. Jung, "Occlusion resistant shape classifier based on warped optimal path matching," Proceedings of IEEE International Conference on Pattern Recognition (IEEE ICPR) (15% oral acceptance rate), vol. 2, pp. 60-63, Hong Kong, Aug. 20-24, 2006.
  • Q. Wen, J. Gao, and K. Luby-Phelps, "Feature selection, matching, and evaluation for subcellular structure tracking," Proceedings of IEEE Engineering in Medicine and Biology Society (IEEE EMBC), pp. 3013-3016, New York, USA, Aug. 30-Sept. 3, 2006.
  • Y. Kim, J. Gao, and P. Michalak, "A new maximum-relevance criterion for significant gene selection," Lecture Notes in Bioinformatics, (IEEE Workshop on Pattern Recognition in Bioinformatics, Hong Kong, Aug 20, 2006), vol.4146, pp. 71-80, Springer Verlag, 2006.
  • Q. Wen, J. Gao, A. Kosaka, H. Iwaki, K. Luby-Phelps, and D. Mundy, "A particle filter framework using optimal importance function for protein molecules tracking," Proc. IEEE International Conference on Image Processing (IEEE ICIP) (acceptance rate 46%), vol.1, pp.1161-1164, Genova, Sept 11-14, 2005.
  • J. Oh and J. Gao, "Peptide identification by tandem mass spectra: an efficient parallel searching," Proceedings of IEEE Symposium on Bioinformatics and Bioengineering (IEEE BIBE) (full paper acceptance rate 18%, 30 out of 164,), pp.161-168, Minneapolis, MN, Oct 19-21, 2005.
  • N. Thakoor and J. Gao, "Shape classification based on generalized Gaussian descent method with hidden Markov model descriptor," Proceedings of IEEE International Conference on Computer Vision (IEEE ICCV) (blind review, acceptance rate: 20.4%, 245 out of 1200), vol.1, pp.495-502, Beijing, China, Oct 15-21, 2005.
  • J. Oh, J. Gao, A. Nandi, P. Gurnani, L. Knowles, J. Schorge, and K. Rosenblatt, "Multicategory classification using extended SVM-RFE and Markov blanket on SELD I-TOF mass Spectrometry data,"Proceedings of IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (IEEE CIBCB), pp. 1-7, San Diego, CA, Nov 14-15, 2005.
  • N. Thakoor and J. Gao, "Automatic video object shape extraction and its classification with camera in motion," Proc. IEEE International Conference on Image Processing (IEEE ICIP), (acceptance rate 46%), vol.3, pp.437-440, Genova, Sept 11-14, 2005.
  • Q. Wen and J. Gao, "Shape-based 3D vascular tree extraction for perforator flaps," Proc. of SPIE Medical Imaging, vol. 5747, pp.1855-1863, San Diego, CA, Feb 12-17, 2005.
  • Y. B. Kim, J. H. Oh, and J. Gao, "Emerging pattern based subspace clustering of microarray gene expression using mixture models," Proceedings of International Conference on Bioinformatics and its Applications (ICBA) (acceptance rate 28%), pp. 13-24, Fort Lauderdale, FL, Dec 16-19, 2004.
  • J. H. Oh, Y.B. Kim, and J. Gao, "A two-way searching algorithm for De Novo peptide sequencing via tandem mass spectrometry," Proceedings of International Conference on Bioinformatics and its Applications (ICBA) (acceptance rate 28%), pp. 402-413, Fort Lauderdale, FL, Dec 16-19, 2004.
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