Conference Program (.pdf)
Monday, May 7, 2007
5:00 – 7:00 pm	Registration and Reception at Atlanta Marriott Downtown (Olympic Ballroom)
Tuesday, May 8, 2007
9:00 – 10:30 am	Parallel Sessions
	1A: Gene expression analysis I (ALC 005) Chair: Qihua Tan	1B: Phylogenetics (ALC 002) Chair: Ion Mandoiu
9:00 am	GFBA: A Biclustering Algorithm for Discovering Value-Coherent Biclusters, Xubo Fei, Shiyong Lu, Horia Pop, Lily Liang	Efficiently Finding the Most Parsimonious Phylogenetic Tree via Linear Programming, Srinath Sridhar, Fumei Lam, Guy Blelloch, R. Ravi, Russell Schwartz
9:30 am	Significance Analysis of Time-Course Gene Expression Profiles, FangXiang Wu	A Multi-Stack Based Phylogenetic Tree Building Method, Robert Busa-Fekete, Andras Kocsor, Csaba Bagyinka
10:00 am	Data-driven Smoothness Enhanced Variance Ratio Test to Unearth Responsive Genes in 0-time Normalized Time-course Microarray Studies, Juntao Li, Jianhua Liu, R. Krishna Murthy Karuturi	A New Linear-time Heuristic Algorithm for Computing the Parsimony Score of Phylogenetic Networks: Theoretical Bounds and Empirical Performance, Guohua Jin, Luay Nakhleh, Sagi Snir, Tamir Tuller
10:30 am	Coffee Break
11:00 – 12:30 pm	Parallel Sessions
	2A: Gene expression analysis II (ALC 005) Chair: Seiya Imoto	2B: Phylogenetics and genomic diversity (ALC 002) Chair: Sanguthevar Rajasekaran
11:00 am	A Bootstrap Correspondence Analysis for Factorial Microarray Experiments with Replications, Qihua Tan	Searching for Recombinant Donors in a Phylogenetic Network of Serial Samples, Patricia Buendia, Giri Narasimhan
11:30 am	Clustering Algorithms Optimizer: A Framework for Large Datasets, Roy Varshavsky, David Horn, Michal Linial	Algorithm for Haplotype Inferring via Galled-tree Networks with Simple Galls, Arvind Gupta, Jan Manuch, Ladislav Stacho, Xiaohong Zhao
12:00 pm	Ranking Function Based on Higher Order Statistics (RF-HOS) for Two-Sample Microarray Experiments, Jahangheer Shaik, Mohammed Yeasin	Estimating Bacterial Diversity from Environmental DNA: A Maximum Likelihood Approach, Yun Lu, Danny Krizanc, Fred Cohan
12:30 pm	Lunch
2:00 – 3:00 pm	Plenary Session (ALC 005)
	Chair: Yi Pan Invited Keynote Talk: Modern Homology Search, Ming Li
3:00 pm	Coffee Break
3:30 – 5:30 pm	Parallel Sessions
	3A: Gene expression analysis III (ALC 005) Chair: R. Krishna Murthy Karuturi	3B: Software tools (ALC 002) Chair: Lonnie Welch
3:30 pm	Statistical Absolute Evaluation of Gene Ontology Terms with Gene Expression Data, Pramod K. Gupta, Ryo Yoshida, Seiya Imoto, Rui Yamaguchi, Satoru Miyano	NEURONgrid: A Toolkit for Generating Parameter-Space Maps using NEURON in a Grid Environment, Robert J Calin-Jageman, Chao Xie, Yi Pan, Art Vandenberg, Paul S. Katz
4:00 pm	Discovering Relations among GO-annotated Clusters by Graph Kernel Methods, Italo Zoppis, Daniele Merico, Marco Antoniotti, Bud Mishra, Giancarlo Mauri	An Adaptive Resolution Tree Visualization of Large Infuenza Virus Sequence Datasets, Leonid Zaslavsky, Yiming Bao, Tatiana Tatusova
4:30 pm	An Empirical Comparison of Dimensionality Reduction Methods for Classifying Gene and Protein Expression Datasets, George Lee, Anant Madabhushi, Carlos Rodriguez	Wavelet Image Interpolation (WII): A Wavelet-based Approach to Enhancement of Digital Mammography Images, Gordana Derado, DuBois Bowman, Rajan Patel, Mary Newell, Brani Vidakovic
5:00 pm		High Level Programming Environment System for Protein Structure Data, Yanchao Wang, Rajshekhar Sunderraman, Piyaphol Phoungphol
5:30 pm	Coffee Break
5:45 – 7:15 pm	Poster Session A		Tutorial A (ALC 005)
	A1. Greedy Approach to Reliable Disease Susceptibility Prediction, Dumitru Brinza, Irina Astrovskaya, and Alexander Zelikovsky A2. Pair wise Alignment of Pathways, Qiong Cheng and Alexender Zelikovsky A3. Toward a Methodology for Discovery of Regulatory Motifs in Plant, Dazhang Gu, Klaus H. Ecker, Lonnie Welch, and Sarah Wyatt A4. Discovering Causal Sentences with Automatically Learned Patterns. Shreekanth Karvaje, Bharat Ravisekar, Baoli Li, and Ashwin Ram A5. An Imputation Method Based on Robust Regression Using Minimum Covariance Determinant Estimates for Cancer Gene Expression Data, Hyunsoo Kim and Haesun Park A6. Design Pattern for Protein Identification, Jens Lichtenberg and Lonnie Welch A7. Characterizing Pseudobase and Predicting RNA secondary structure with simple H-type pseudoknots, Oyun-Erdene Namsrai A8. Mining MEDLINE for Gene Clustering: A Comparison of Feature Selection Approaches. Sailaja Pydimarri, Orlando Karam, Venu Dasigi, and Rajnish Singh A9. Evaluation of Stability Changes in Single Point Protein Mutants Using a Four-body Statistical Potential, Gregory Reck and Iosif Vaisman A10. A Topological Characterization of Protein-Water Interactions for Knowledge-Based Models, Gregory Reck and Iosif Vaisman A11. Integrated Statistical and Association Rule Analyses of Time-Dependent Gene Co-expression Patterns, Sandra Rodriguez-Zas, Younhee Ko, and Bruce Southey A12. A Bioinformatics Approach to the Identification, Classification, and Analysis of Plant Hydroxyproline-Rich Glycoproteins, Allan M. Showalter, Brian Keppler, Jason Yerardi, Tom Conley, Lonnie R. Welch, and Dazhang Gu		Scalable Algorithms for Genotype and Haplotype Analysis Ion Mandoiu and Alexander Zelikovsky Abstract. In diploid organisms such as humans, there are two non-identical copies of each autosomal chromosome, one inherited from the mother and one inherited from the father. The combinations of SNP alleles in the maternal and paternal chromosomes are referred to as the individual's haplotypes. Although it is possible to directly determine the haplotypes of an individual by experimental techniques, such methods are prohibitively expensive and time consuming. In contrast, there are many cost-effective high-throughput techniques for determining the conflated SNP information called genotype, which specifies the identities of the two alleles at each SNP position, but does not assign the alleles to specific chromosomes for SNP loci at which the individual has two different alleles. Renewed interest in algorithms for genotype and haplotype analysis is currently fueled by the need to handle increasingly larger datasets. High-end genotyping platforms from Affymetrix and Illumina already allow typing over half a million SNP genotypes per experiment, with one million SNP genotypes per experiment expected in the very near future. Furthermore, due to decreasing genotyping costs, future association studies are expected to comprise thousands of typed individuals. Many of the commonly used analysis methods are vastly inadequate for handling datasets of the size envisioned to be produced by the next generation of genome-wide association studies. In this tutorial we review recent progress on scalable algorithms for genotype and haplotype analysis, including algorithms for haplotype inference, genotype error detection, genotype tagging and indexing, disease association search, and disease susceptibility prediction.
Wednesday, May 9, 2007
9:00 – 10:30 am	Parallel Sessions
	4A: Gene selection (ALC 005) Chair: Dumitru Brinza	4B: Motif finding I (ALC 002) Chair: Giri Narisimhan
9:00 am	Finding Minimal Sets of Informative Genes in Microarray Data, Kung-Hua Chang, Yong Kyun Kwon, D. Stott Parker	Space and Time Efficient Algorithms to Discover Endogenous RNAi Patterns In Complete Genome Data, Sudha Balla, Sanguthevar Rajasekaran
9:30 am	Noise-based Feature Perturbation as a Selection Method for Microarray Data, Li Chen, Dmitry Goldgof, Lawrence Hall, Steven Eschrich	A Fast Approximate Covariance-Model-Based Database Search Method for Non-coding RNA, Scott Smith
10:00 am	Efficient Generation of Biologically Relevant Enriched Gene Sets, Igor Trajkovski, Nada Lavrac	Extensions of Naive Bayes and their Applications to Bioinformatics, Raja Loganantharaj
10:30 am	Coffee Break
11:00 – 12:30 pm	Parallel Sessions
	5A: Genome analysis I (ALC 005) Chair: Liqing Zhang	5B: Motif finding II (ALC 002) Chair: Sanguthevar Rajasekaran
11:00 am	The solution Space of Sorting by Reversals, Marilia D.V. Braga, Marie-France Sagot, Celine Scornavacca, Eric Tannier	Enhancing Motif Refinement by Incorporating Comparative Genomics Data, Erliang Zeng, Giri Narasimhan
11:30 am	A Fast and Exact Algorithm for the Perfect Reversal Median Problem, Matthias Bernt, Daniel Merkle, Martin Middendorf	Mining Discriminative Distance Context of Transcription Factor Binding Sites on ChIP Enriched Regions, Hyunmin Kim, Katherina Kechris, Lawrence Hunter
12:00 pm	Genomic Signatures from DNA Word Graphs, Lenwood Heath, Amrita Pati	Enhanced Prediction of Cleavage in Bovine Precursor Sequences, Allison Tegge, Sandra Rodriguez-Zas, Bruce Southey
12:30 pm	Lunch
2:00 – 3:00 pm	Plenary Session (ALC 005)
	Chair: Jack Yang Invited Keynote Talk: A Computational Study of Bidirectional Promoters in the Human Genome, Laura L. Elnitski
3:00 pm	Coffee Break
3:30 – 5:00 pm	Parallel Sessions
	6A: Genome analysis II (ALC 005) Chair: Lenwood Heath	6B: Motif finding III (ALC 002) Chair: Leonid Zaslavsky
3:30 pm	The Identification of Antisense Gene Pairs through Available Software, Mark Lawson, Liqing Zhang	Predicting Palmitoylation Sites Using A Regularised Bio-Basis Function Neural Network, Ron Yang
4:00 pm	Inferring Weak Adaptations and Selection Biases in Proteins from Composition and Substitution Matrices, Steinar Thorvaldsen, Elinor Ytterstad, Tor Fla	A Novel Kernel-based Approach for Predicting Binding Peptides for HLA Class II Molecules, Hao Yu, Minlie Huang, Xiaoyan Zhu, Yabin Guo
4:30 pm	Markov Model Variants for Appraisal of Coding Potential in Plant DNA, Michael Sparks, Volker Brendel, Karin Dorman	A Database for Prediction of Unique Peptide Motifs as Linear Epitopes, Tun-Wen Pai, Margaret Dah-Tsyr Chang, Wen-Shyong Tzou
5:00 pm	Coffee Break
5:15 – 6:45 pm	Poster Session B		Tutorial B (ALC 005)
	B1. CABIN: Collective Analysis of Biological Interaction Network, Mudita Singhal and Kelly Domico B2. Smoothing spline mixed effects modeling of multi-factorial gene expression profiles, Brandon Smith, Bruce Southey, and Sandra Rodriguez-Zas B3. DeltaProt: Molecular comparison of proteins based on sequence alignments, Steinar Thorvaldsen, Tor Flе, and Nils P Willassen B4. Using Logical Sets to Target Gene Expression Patterns, Timothy Tickle and M. Taghi Mostafavi B5. Database for Structural Analysis of HIV Protease, Yunfeng Tie, Hao Wang, Robert Harrison, and Irene Weber B6. A integrated solution based on distance method for reconstructing phylogenetic trees, Cristianno Vieira, Glauber Gongcalves, and Martha Torres B7. A Survey of Basecalling Algorithms, Andy Ju An Wang B8. Ordered Combinatorial Feature Selection : An Information Portal for Multiple Indexing Sequence Alignment, Hsin-Wei Wang, Jian-Ming Chen, Wei-Yao Chou, Margaret Dah-Tsyr Chang, and Tun-Wen Pai B9. Positional Clustering of Neighboring Genes in the Zebrafish Genome, Wei Wu, Jinrong Peng, and Louxin Zhang B10. Co-evolution Analysis of Protein Complexes and Its Applications in Pairing Preferences Prediction, FangFang Pan, Dongsheng Che, Michelle Momany, Liming Cai, and Russell Malmberg B11. Unbiased Validation of Multiple Linear Regression Tagging, Jingwu He, Jun Zhang, and Alexander Zelikovsky		Protein Structural Prediction with Broad Initiatives in Bioinformatics Research and Applications Jack Yang and Mary Qu Yang Abstract. Proteins are composed of one or more chains of amino acids, and exhibit several levels of structure. Many protein regions and some entire proteins lack specific 3-D structures, existing as dynamic, disordered ensembles under physiological conditions. Intrinsically Unstructured regions and disordered Proteins (IUP) affect protein folding pathways and ligand bindings. Recently, IUP are gaining more and more attention in medicinal and pharmaceutical studies, because IUP have been associated with a wide range of protein functions. IUP are also playing central roles in diseases characterized by protein misfolding and aggregation. Knowledge of IUP can help in determination of protein function and effective drug design and discovery. Although IUP can be identified by laborious and time-consuming methods such as X-ray crystallography, NMR and CDR, computational methods predicting IUP from the primary structure of a protein which are essential for automated structural and functional prediction and annotation of proteins as well as drug design and discovery. Our basic approach consists in applying a hybrid unsupervised-supervised classifier called the Recursive Maximum Contrast Tree (RMCT) classifier to this problem, in combination with novel feature generation, feature selection techniques and ensemble methods. This tutorial will discuss the effectiveness of the approaches to learning protein structural classes, and also provide comparisons to more traditional classifiers such as neural networks and support vector machines.
7:10 pm	Banquet at Atlanta Marriott Downtown (Centennial Ballroom)
Thursday, May 10, 2007
9:00 – 10:30 am	Parallel Sessions
	7A: Sequence analysis (ALC 005) Chair: Mary Qu Yang	7B: Cancer Classification (ALC 002) Chair: Wei Zhong
9:00 am	A Novel Greedy Algorithm for the Minimum Common String Partition Problem, Dan He	Cancer Class Discovery using Non-negative Matrix Factorization based on Alternating Non-negativity-constrained Least Squares, Hyunsoo Kim, Haesun Park
9:30 am	An Efficient Algorithm for Finding Gene-specific Probes for DNA Microarrays, Mun-Ho Choi, Seung-Ho Kang, In-Seon Jeong, Hyeong-Seok Lim	A Support Vector Machine Ensemble for Cancer Classification using Gene Expression Data, Chen Liao, Shutao Li
10:00 am	Multiple Sequence Local Alignment Using Monte Carlo EM Algorithm, Chengpeng Bi	Combining SVM Classifiers Using Genetic Fuzzy Systems based on AUC for Gene Expression Data Analysis, Xiujuan Chen, Yichuan Zhao, Yan-Qing Zhang, Robert Harrison
10:30 am	Coffee Break
11:00 – 12:30 pm	Parallel Sessions
	8A: RNA and protein structure (ALC 005) Chair: Luciano Margara	8B: Clustering and Classification (ALC 002) Chair: Lawrence Hall
11:00 am	A BP-SCFG Based Approach for RNA Secondary Structure Prediction with Consecutive Bases Dependency and Their Relative Positions Information, Dandan Song, Zhidong Deng	Coclustering Based Parcellation of Human Brain Cortex Using Diffusion Tensor MRI, Cui Lin, Shiyong Lu, Danqing Wu
11:30 am	Delta: a Toolset for the Structural Analysis of Biological Sequences on a 3D Triangular Lattice, Minghui Jiang, Martin Mayne, Joel Gillespie	An Algorithm for Hierarchical Classification of Genes of Prokaryotic Genomes, Hongwei Wu, Fenglou Mao, Victor Olman, Ying Xu
12:00 pm	Statistical Estimate for the Size of the Protein Structural Vocabulary, Xuezheng Fu, Bernard Chen, Yi Pan, Robert Harrison	Using Multi Level Nearest Neighbor Classifiers for G-protein Coupled Receptor Sub-families Prediction, Mudassir Fayyaz, Adnan Mujahid Khan, Asifullah Khan, Alex Kavokin
12:30 pm	Lunch
2:00 – 3:00 pm	Plenary Session (ALC 005)
	Chair: Alex Zelikovsky Invited Keynote Talk: Ab initio Gene Finding Engines: What is Under the Hood, Mark Borodovsky
3:00 pm	Coffee Break
3:30 – 5:00 pm	Parallel Sessions
	9A: Protein structure and nucleosome dynamics (ALC 005) Chair: Wei Zhong	9B: Gene networks, pathways, and protein domain interactions (ALC 002) Chair: Hongwei Wu
3:30 pm