Program (update 11/4)
December 4, 2011
Tutorial Sessions
6:30 pm to 9:00 pm
Time: 1:00 am to 5:30 am
Reception
December 5, 2011
Session: 1
7:50 am
Opening remark
8:00 am to 9:30 am
Plenary talks
9:30 am to 9:50 am
Break & posters
Next Generation Sequencing for Epigenetic Research
Time: 9:50 am to 11:50 am
1. A Scalable, Flexible Workflow for MethylCap-Seq Data Analysis
Benjamin Rodriguez1, Hok-Hei Tam1, David Frankhouser1, Michael Trimarchi1, Mark Murphy1, Chris Kuo1, Deval Parikh1, Bryan
Ball1, Sebastian Schwind1, John Curfman1, William Blum1, Guido Marcucci1, Pearlly Yan1, Ralf Bundschuh2
1. The Ohio State University Comprehensive Cancer Center Columbus, Ohio, USA,
2. Departments of Physics and Biochemistry, Center for RNA Biology, The Ohio State University Columbus, Ohio, USA.
2. An ERα/Modulator Regulatory Network in the Breast Cancer Cells
Heng-Yi Wu1, Yu Wang1, P. Zheng1, G. Jiang1, Yunlong Liu1, Kenneth P. Nephew2, Tim H. M. Huang3, Lang Li4
1. Center for Computational Biology and Bioinformatics Indiana University Indianapolis, Indiana USA
2. Medical Sciences, School of Medicine Indiana University Bloomington, Indiana USA
3. Department of Molecular Virology, Immunology, and Medical Genetics The Ohio State University Columbus, Ohio USA
4. Department of Medical and Molecular Genetics Indiana University Indianapolis, Indiana USA.
3. Empirical Bayes Model Comparisons for Differential Methylation Analysis
Mingxiang Teng1, Yadong Wang1, Curt Balch2, Kenneth P. Nephew2, Yunlong Liu3, Lang Li4, Seongho Kim5
1. School of Computer Science and Technology Harbin Institute of Technology Harbin, Heilongjiang, China
2. Medical Sciences Indiana University Bloomington, Indiana, USA
3. Department of Medicine, Indiana University Indianapolis, Indiana, USA
4. Department of Medical and Molecu-lar Genetic, Indiana University Indianapolis, Indiana, USA
5. Department of Bioinformatics and Biostatistics University of Louisville, Louisville, Kentucky, USA.
4. Chromatin signature analysis and prediction of genome-wide novel promoters using finite mixture model
Cenny Taslim1, Shili Lin1, Kun Huang2, Tim Huang3
1. Department of Statistics Columbus, OH 43210, USA.
2. Department of Biomedical Informatics, Columbus, OH 43210, USA.
3. Department of Molecular Virology, Immunology and Medical Genetics Columbus, OH 43210, USA.
5. Enabling Atlas2 Personal Genome Analysis on the Cloud
Uday S. Evani1,4, Danny Challis1, Jin Yu1, Andrew R. Jackson2,3, Sameer Paithankar2,3, Matthew N. Bainbridge1, Cristian Coar-fa2,3,
Aleksandar Milosavljevic2,3,4, Fuli Yu1,3,4
1. The Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA.
2.Bioinformatics Research Laboratory, Epigenome Center, Department of Molecular and Human Genetics.
3. Department of Molecular and Human Genetics, Baylor College of Medicine, TX 77030, USA.
4. Corresponding authors.
6. A Novel Approach for Alignments Output Storage Problem Facing Clinical Scenarios
Yiqi Lu1, Yaoliang Chen2, Fuli Yu3, Yanghua Xiao4, Danfeng Xu5
1. School of Computer Science, Fudan University Shanghai 200433, PR China.
2. School of Computer Science, Fudan University Shanghai 200433, PR China.
3. The Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030 USA.
4. School of Computer Science, Fudan University Shanghai 200433, PR China. (Corresponding Author)
5. School of Computer Science, Fudan University Shanghai 200433, PR China.
Session: 2
Gene Regulation Network I
Time: 9:50 am to 11:50 am
1. Uncertainty-based Essentiality in Gene Regulatory Networks
Xiaoning Qian1, Byung-Jun Yoon2 and Edward R. Dougherty2,3,4,
1. Dept. of Computer Science & Engineering, University of South Florida, Tampa, FL 33620
2. Dept. of Electrical & Computer Engineering, Texas A&M University, College Station, TX 77843
3. Computational Biology Division, Translational Genomics Research Institute, Phoenix, AZ 85004
4. Dept. of Bioinformatics and Computational Biology,University of Texas M. D. Anderson Cancer Center, Houston, TX 77030
2. The effect of certain Boolean functions in stability of networks with varying topology
Vitor H. P. Louzada1, Ronaldo F. Hashimoto1,Fabr´ıcio M. Lopesy2.
1. Institute of Mathematics and Statistics of the University of S˜ao Paulo, Brazil
2. Federal University of Technology - Paran´a, Brazil
3. Modelling Oxidative Stress Response Pathways
Sriram Sridharan1, Ritwik Layek1, Aniruddha Datta1, Jijayanagaram Venkatraj2
1. Texas A & M University, Electrical and Computer Engineering, College Station, TX, 77843-3128, USA.
2. Texas A & M University, Vet Integrative Biosciences, College Station, TX, 77843-4458, USA.
4. A novel critical time analysis approach for Genetic Regulatory Networks
Sonal Bhattacharya, Ranadip Pal
Electrical and Computer Engineeirng Department, Texas Tech University, Lubbock, TX, USA
5. Inference of a Genetic Regulatory Network model from limited time series data
Saad Haider, Ranadip Pal
Texas Tech UniversityLubbock, TX, 79409, USA.
6. A Cubature Kalman Filter Approach for Inferring Gene Regulatory Networks Using Time Series Data
Amina Noor1, Erchin Serpedin1, Mohamed Nounou2 and Hazem Nounou2
1. Department of Electrical and Computer Engineering Texas A&M University, College Station, Texas 77843.
2. Texas A&M University at Qatar, Doha, Qatar 23874.
1:20 pm to 2:00 pm
Round Table with funding agencies.
Session: 3
Computational Methods for Therapeutic
Time 2:00 pm to 4:00 pm
1. Efficient Combinatorial Drug Optimization Through Stochastic Search
Mansuck Kim, Byung-Jun Yoon
Department of Electrical and Computer Engineering Texas A&M University.
2. A novel approach for tumor sensitivity prediction and combination therapy design for targeted drugs
Noah Berlow, Ranadip Pal.
Texas Tech University Lubbock, TX, 79409, USA.
3. Modeling Cyclic and Acyclic Therapeutic Methods with Persistent Intervention Effect in Probabilistic Boolean
Networks
Mohammadmahdi R. Yousefi1, Aniruddha Datta1, Edward R. Dougherty1,2,3
1. Dept. of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA.
2. Comp. Biology Division, Translational Genomics Research Institute, Phoenix, AZ, USA.
3. Dept. of Bioinf. and Comp. Biology, University of Texas M. D. Anderson Cancer Center, Houston, TX, USA.
4. Predicting Drug Efficacy Based on the Integrated Breast Cancer Pathway Model
Hui Huang1, Xiaogang Wu1, Sara Ibrahim2 , Marianne McKenzie3, Jake Y. Chen4
1.School of Informatics, Indiana University.
2. School of Medicine Indiana University.
3. School of Science Purdue University.
4. School of Informatics Indiana University.
5. Identifying Genes Associated with Chemotherapy Response in Ovarian Carcinomas Based on DNA Copy Number
and Expression Profiles
Fang-Han Hsu1, Erchin Serpedin1, Tzu-Hung Hsiao3, Alexander J.R. Bishop3,4, Edward R. Dougherty1,2, Yidong Chen3,5
1.Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX.
2.Computational Biology Division, Translational Genomics Research Institute, Phoenix, AZ.
3.Greehey Children’s Cancer Research Institute.
4.Department of Cellular and Structural Biology.
5.Department of Epidemiology and Biostatistics, University of Texas Health Science Center at San Antonio, San Antonio, TX.
6. Assessing the Efficacy of Molecularly Targeted Agents by Using Kalman Filter
Xiangfang (Lindsey) Li, Lijun Qian, Michael L. Bittner, and Edward R. Dougherty
Session: 4
Drug Selection Gene Regulation Network II
Time 2:00 pm to 4:00 pm
1. Probabilistic consistency transformation for multiple alignment of biological networks
Sayed Mohammad Ebrahim Sahraeian, Byung-Jun Yoon
Department of Electrical & Computer Engineering Texas A&M University, College Station, TX 77843-3128, USA.
2. Attractor Estimation and Model Refinement for Stochastic Regulatory Network Models
Jason Knight1, Edward Dougherty1, 2
1. Dept. of Electrical and Computer Engineering, Texas A&M University College Station, Texas 77843 USA
2. Computational Biology Division, Translational Genomics Research Institute, Phoenix, Arizona 85004 USA.
3. Steady state probability approximation applied to stochastic model of biological network
Md. Shahriar Karim, David M. Umulis and Gregery T. Buzzard.
4. Identification of biomarkers in breast cancer metastasis by integrating protein-protein interaction network
and gene expression data
Md Jamiul Jahid, Jianhua Ruan
Department of Computer Science The University of Texas at San Antonio San Antonio, USA
5. Pathway Analysis in the Context of Bayesian Networks - Mathematical Modeling of Master and Canalizing Genes
Chen Zhao1,2, Ivan Ivanov3, Michael L. Bittner2, Edward R.Dougherty1, 2, 4
1. Dept. of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA.
2. Computational Biology Division, Translational Genomics Research Institute, Phoenix, AZ, USA.
3. Dept. of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, TX, USA.
4. Dept. of Bioinformatics and Computational Biology, University of Texas M. D. Anderson Cancer Center, Houston, TX, USA.
6. Gene Network Inference via Sparse Structural Equation Modeling with Genetic Perturbations
Xiaodong Cai1, Juan Andr´es Bazerque2, Georgios B. Giannakis2.
1.Dept. of ECE, Univ. of Miami Coral Gables, FL 33146, USA.
2.Dept. of ECE, Univ. of Minnesota, Minneapolis, MN 55455, USA.
4:00 pm to 4:20 pm
Session: 5
Break & posters
Data Integration
Time 4:20 pm to 6:20 pm
1. Improvement of GNs inference through biological data integration
F´abio Fernandes da Rocha Vicente1;2, Fabr´ıcio M. Lopes1, Ronaldo F. Hashimoto2
1. Federal University of Technology - Paran´a, Brazil
2. Institute of Mathematics and Statistics, University of S˜ao Paulo, Brazil
2. Multisource Biological Pathway Consolidation
Mark S. Doderer1, Zachry Anguiano1, Uthra Suresh1, Ravi Dashnamoorthy1, Alexander J.R. Bishop1, 2, 4, and Yidong Chen1, 3, 4
1.Greehey Children’s Cancer Research Institute.
2.Department of Cellular and Structural Biology.
3. Department of Epidemiology and Biostatistics, and
4.Cancer Therapy & Research Center, The University of Texas Health Science Center at San Antonio San Antonio, USA.
3. A Method For Finding Novel Associations Between Genome-Wide Copy Number And DNA Methylation Patterns
Man-Hung Eric Tang1, Vinay Varadan2, Sid Kamalakaran2, Michael Q. Zhang3 , Nevenka Dimitrova2, James Hicks1
1. Cold Spring Harbor Laboratory, 1 Bungtown Rd, NY 12724, USA
2. Philips Research North America, 345 Scarborough Rd, Briarcliff Manor, NY 10510, USA
3. The University of Texas at Dallas, Richardson TX 75080, USA and Tsinghua University, Beijing, 100084 China.
4. Stochastic Modeling of Dynamic Effects of Copy Number Alterations upon Gene Expression Levels
Fang-Han Hsu1, Erchin Serpedin1, Yidong Chen2,3, and Edward R. Dougherty1, 4
1. Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX.
2. Department of Epidemiology and Biostatistics, University of Texas Health Science Center at San Antonio, San Antonio, TX.
3. Greehey Children’s Cancer Research Institute, University of Texas Health Science Center at San Antonio, San Antonio, TX.
4. Computational Biology Division, Translational Genomics Research Institute, Phoenix, AZ.
5. Efficient Cancer Therapy using Boolean Networks and Max-SAT-based ATPG
Pey-Chang Kent Lin, Sunil P. Khatri
Department of ECE, Texas A&M University, College Station TX 77843
6. Designing Enhanced Classifiers Using Prior Process Knowledge: Regularized Maximum-Likelihood
Mohammad Shahrokh Esfahani1, Amin Zollanvari2, Byung-Jun Yoon1, and Edward R. Dougherty1,3
1.Department of Electrical and Computer Engineering, Texas A&M University.
2. Childrens Hospital Informatics Program at Harvard-MIT Division of Health Sciences and Technology, Harvard Medical School,
Brigham and Womens Hospital.
3. Computational Biology Division, Translational Genomics Research Institute (TGen), Phoenix, Arizona, USA.
Session: 6
Proteomics data processing
Time 4:20 pm to 6:20 pm
1. Finding Effective Subnetwork Markers for Cancer by Passing Messages
Byung-Jun Yoon
Department of Electrical and Computer Engineering Texas A&M University, College Station, TX.
2. Application of Survival Analysis Methodology to the Quantitative Analysis of LC-MS Proteomics Data
Carmen D. Tekwe, Alan R. Dabney, Raymond J. Carroll
Department of Statistics Texas A & M University College Station, TX 77843-3143
3. Mapping of International Protein Index to Affymetrix Probe-Set Identifier for Correlating Genomics and
Proteomics Expression Profiles in Multiple Myeloma
Shweta S. Chavan 1,2, John D. Shaughnessy Jr.1, Bart Barlogie1, Ricky D. Edmondson1
1.Myeloma Institute for Research and Therapy, University of Arkansas Medical Sciences (UAMS), 4301 W. Markham Street,
Slot#776, Little Rock, AR 72205, USA.
2. University of Arkansas Little Rock–UAMS Joint Bioinformatics Program, 2801 S. University Avenue, Little Rock, AR 72204, USA.
4. Multiple Reaction Monitoring: Modeling and Systematic Analysis
Esmaeil Atashpaz-Gargari1, Ulisses M. Braga-Neto1, and Edward R. Dougherty1;2;3
1. Dept. of Electrical and Computer Engineering, Texas A&M University.
2. Computational Biology Division, Translational Genomics Research Institute, Phoenix, AZ.
3. Dept. of Bioinformatics and Computational Biology, University of Texas M. D. Anderson Cancer Center, Houston, TX.
5. Joint Corresponding Feature Identification and Alignment for Multiple LC/MS Replicates
Jian Cui, Xuepo Ma, Jianqiu(Michelle) Zhang
Department of Electrical and Computer Engineering University of Texas at san Antonio San Antonio, Texas 78249.
6. Modeling and systematic analysis of LC-MS proteomics pipeline
Youting Sun1, Ulisses Braga-Neto1, Edward R. Dougherty1;2;3
1. Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX.
2. Computational Biology Division, Translational Genomics Research Institution, Phoenix, AZ.
3. Department of Bioinformatics and Computational Biology, University of Texas M.D. Anderson Cancer Center, Houston, TX
6:30 pm to 9:00 pm
Banquet
December 6, 2011
8:00 am to 9:30 am
Plenary talks
9:30 am to 9:50 am
Break & posters
Session: 7
Clustering and Classification Methods
Time 9:50 am to 11:50 am
1. Classifier Error Estimator Performance in a Bayesian Context
Lori Dalton1, Edward R. Dougherty1, 2, 3
1.Dept. of Electrical and Computer Engineering, Texas A&M University, College Station, TX USA.
2.Computational Biology Division, Translational Genomics Research Institute, Phoenix, AZ USA.
3. Dept. of Bioinf. and Computational Biology, University of Texas M. D. Anderson Cancer Center, Houston, TX USA.
2. Sample-Based Estimators for the Intrinsically Multivariate Prediction Score
Ting Chen, Ulisses Braga-Neto
Department of Electrical Engineering Texas A & M University College Station, Texas 77843
3. Clustering Gene Expression Data using Probabilistic Non-negative Matrix Factorization
Belhassen Bayar1, Nidhal Bouaynaya2, Roman Shterenberg3
1.Department of Electrical Engineering Ecole Nationale d’Ing´enieurs de Tunis, Tunisia.
2. Department of Systems Engineering University of Arkansas at Little Rock, USA.
3. Department of Mathematics University of Alabama at Birmingham, USA.
4. Relationship between the accuracy of classifier error estimation and distribution complexity
Esmaeil Atashpaz-Gargari1, Chao Sima2, Ulisses M. Braga-Neto1, and Edward R. Dougherty1, 2, 3
1. Dept. of Electrical and Computer Engineering, Texas A&M University.
2. Computational Biology Division, Translational Genomics Research Institute, Phoenix, AZ.
3. Dept. of Bioinformatics and Computational Biology, University of Texas M. D. Anderson Cancer Center, Houston, TX.
5.
Geometrical Modification Of Wavelet SVM Kernels And Its Application In Microarray Analysis
Hong Cai , Yufeng Wang
Department of Biology University of Texas at San Antonio, San Antonio, TX 78249, USA.
6. S-score : a Novel Scoring Method of Gene Signatures for Molecular Classification
Hung-I Harry Chen1, Tzu-Hung Hsiao1, Yidong Chen1, 2, Charles Keller3
1.Greehey Children’s Cancer Research Institute
2.Department of Epidemiology and Biostatistics, University of Texas Health Science Center at San Antonio, San Antonio, Texas
3. Pediatric Cancer Biology Program, Pap Papé Family Pediatric Research Institute Family Pediatric Research Institute,Department
of Pediatrics, Oregon Health and Science University, Portland, Oregon.
Session: 8
MicroRNA, GWAS, Next-Generation Sequencing Methods
Time 9:50 am to 11:50 am
1. Computational Prediction of microRNA Regulatory Pathways
Dong Yue1, Yidong Chen2, Shou-Jiang Gao2, Yufei Huang1, 2
1. Department of Electrical and Computer Engineering, University of Texas at San Antonio, U.S.
2. Greehey Children’s Cancer Research Institute, University of Texas Health Science Center at San Antonio, U.S.
2. A Sequential Monte Carlo Base-calling Method for next-generation DNA Sequencing
Xiaohu Shen and Haris Vikalo
Department of Electrical and Computer Engineering, University of Texas at Austin
3. Personal Genome Privacy Protection with Feature-based Hierarchical Dual-stage Encryptions
Xukai Zou1, Peng Liu2, Jake Y. Chen3
1. Department of Computer & Information Science Purdue University Indianapolis, IN 46202, USA.
2. College of Information Science and Technology Penn State University, University Park, PA 16802, USA.
3. School of Informatics Indiana University Indianapolis, IN 46202, USA.
4. Beyond Seed Match: Improving miRNA Target Prediction using PAR-CLIP Data
Mingzhu Lu1, C. L. Philip Chen2, Yufie Huang1
1. Department of Electrical and Computer Engineering, The University of Texas at San Antonio, TX, USA.
2. Faculty of Science of Technology, University of Macau, China.
5. Network-assisted Causal Gene Detection in Genome-wide Association Studies: An Improved Module Search
Algorithm
Peilin Jia1, Zhongming Zhao1, 2, 3
1. Department of Biomedical Informatics.
2. Department of Psychiatry
3. Department of Cancer Biology Vanderbilt University School of Medicine Nashville TN 37232, USA.
6. Comparative Copy Number Variation from Whole Genome Sequencing
Angel Janevski, Vinay Varadan, Sitharthan Kamalakaran, Nilanjana Banerjee, Nevenka Dimitrova
Philips Research, 345 Scarborough Rd, Briarcliff Manor, NY 10510.
Session: 9
ISIMB 2011
Time 9:50 am to 11:50 am
1. ECF sigma factor-associated regulatory networks in Streptomyces colicolor A3(2)
Zhan Zhou1, 2, Qi Li1, Julie Tudyk1, Yong-Quan Li2 and Yufeng Wang1, 3
1. Department of Biology, University of Texas at San Antonio, San Antonio, TX 78249, USA.
2. College of Life Sciences, Zhejiang University, Hangzhou 310058, P. R. China.
3. South Texas Center for Emerging Infectious Diseases, University of Texas at San Antonio, San Antonio, TX 78249, USA.
2. A Compton scattering suppression based Image reconstruction method for digital brest tomosynthesis
Shiyu Xu and Ying Chen
3. Effects of slice thickness filter in filtered backprojection reconstruction with parallel breast tomosynthesis
imaging configuration
Linlin Cong1, Weihua Zhou2, Ying Chen3
1. Biomedical Engineering Graduate Program, Southern Illinois University.
2. Department of Electrical and Computer Engineering, Southern Illinois University, Carbondale, IL 62901.
3. Corresponding Author.
4. Transcriptomic analysis using svd clustering and svm classification
Hong Cai , Yufeng Wang
Department of Biology University of Texas at San Antonio, San Antonio, TX 78249, USA
5. Targeting myocardial infarction-specific protein interactions using computational analyses
Nguyen Nguyen1, Xiaolin Zhang1, Yunji Wang1, Hai-Chao Han1, Yufang Jin1, Galen Schmidt2, Richard A. Lange3, Robert J. Chilton3,
Merry Lindsey3
1. Dept. of ECE University of Texas at San Antonio San Antonio, TX 78249, USA.
2. Dept. of ECE Rice University Houston, TX 77005, USA.
3. Dept. of Medicine University of Texas Health Science Center at San Antonio San Antonio, TX 78229, USA.
6. Mathematical modeling of macrophage activation in left ventricular remodeling post-myocardial infarction
Yunji Wang1, Yufang Jin1, Yonggang Ma2, Ganesh V Halade2, Merry L. Linsey2
1. Department of Electrical and Computer Engineering, University of Texas at San Antonio San Antonio, Texas 78249, USA.
2. Department of Medicine-Cardiology University of Texas Health Science Center at San Antonio San Antonio, TX 78229, USA
1:00 pm to 5:00 pm
Hands-on workshop on next Gen-sequencing
By Texas Advanced Computing Center