Pattern Recognition in Bioinformatics

1. Front Matter

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2. Sequence Analysis

   1. Automated Methods of Predicting the Function of Biological Sequences Using GO and Rough Set

      • Xu-Ning Tang, Zhi-Chao Lian, Zhi-Li Pei, Yan-Chun Liang

      Pages 1-10

   2. C-Based Design Methodology for FPGA Implementation of ClustalW MSA

      • Yan Lin Aung, Douglas L. Maskell, Timothy F. Oliver, Bertil Schmidt, William Bong

      Pages 11-18

   3. A Two-Phase ANN Method for Genome-Wide Detection of Hormone Response Elements

      • Maria Stepanova, Feng Lin, Valerie C. -L. Lin

      Pages 19-29

   4. An Expert Knowledge-Guided Mutation Operator for Genome-Wide Genetic Analysis Using Genetic Programming

      • Casey S. Greene, Bill C. White, Jason H. Moore

      Pages 30-40

   5. cDNA-Derived Amino Acid Sequence from Rat Brain A2aR Possesses Conserved Motifs PMNYM of  TM 5 Domain, Which May Be Involved in Dimerization of A2aR

      • Pratibha Mehta Luthra, Sandeep Kumar Barodia, Amresh Prakash, Ramraghubir

      Pages 41-50

   6. Strong GC and AT Skew Correlation in Chicken Genome

      • Xuegong Deng, Xuemei Deng, Ilkka Havukkala

      Pages 51-59

   7. Comparative Analysis of a Hierarchical Bayesian Method for Quantitative Trait Loci Analysis for the Arabidopsis Thaliana

      • Caroline Pearson, Susan J. Simmons, Karl Ricanek Jr., Edward L. Boone

      Pages 60-70

3. Prediction of Protein Structure, Interaction and Localization

   1. Using Decision Templates to Predict Subcellular Localization of Protein

      • Jianyu Shi, Shaowu Zhang, Quan Pan, Yanning Zhang

      Pages 71-83

   2. Generalized Schemata Theorem Incorporating Twin Removal for Protein Structure Prediction

      • Md Tamjidul Hoque, Madhu Chetty, Laurence S. Dooley

      Pages 84-97

   3. Using Fuzzy Support Vector Machine Network to Predict Low Homology Protein Structural Classes

      • Tongliang Zhang, Rong Wei, Yongsheng Ding

      Pages 98-107

   4. SVM-BetaPred: Prediction of Right-Handed ß-Helix Fold from Protein Sequence Using SVM

      • Siddharth Singh, Krishnan Hajela, Ashwini Kumar Ramani

      Pages 108-119

   5. Protein Fold Recognition Based Upon the Amino Acid Occurrence

      • Y. -h. Taguchi, M. Michael Gromiha

      Pages 120-131

   6. Using Efficient RBF Network to Identify Interface Residues Based on PSSM Profiles and Biochemical Properties

      • Yu-Yen Ou, Shu-An Chen, Chung-Lu Shao, Hao-Geng Hung

      Pages 132-141

   7. Dynamic Outlier Exclusion Training Algorithm for Sequence Based Predictions in Proteins Using Neural Network

      • Shandar Ahmad

      Pages 142-147

   8. Bioinformatics on β-Barrel Membrane Proteins: Sequence and Structural Analysis, Discrimination and Prediction

      • M. Michael Gromiha

      Pages 148-157

   9. Estimation of Evolutionary Average Hydrophobicity Profile from a Family of Protein Sequences

      • Said Hassan Ahmed, Tor Flå

      Pages 158-165

4. Gene Expression Analysis

   1. APMA Database for Affymetrix Target Sequences Mapping, Quality Assessment and Expression Data Mining

      • Yuriy Orlov, Jiangtao Zhou, Joanne Chen, Atif Shahab, Vladimir Kuznetsov

      Pages 166-177

   2. Ensemble of Dissimilarity Based Classifiers for Cancerous Samples Classification

      • Ángela Blanco, Manuel Martín-Merino, Javier de las Rivas

      Pages 178-188

   3. Gene Expression Analysis of Leukemia Samples Using Visual Interpretation of Small Ensembles: A Case Study

      • Gregor Stiglic, Nawaz Khan, Mateja Verlic, Peter Kokol

      Pages 189-197

The advancements of computational and informational techniques have enabled in silico testing of many lab-based experiments in life sciences before performing them in in vitro or in vivo. Though computational techniques are not capable of mimicking all wet-lab experiments, bioinformatics will inevitably play a major role in future medical practice. For example, in the pursuit of new drugs it can reduce the costs and complexity involved in expensive wet-lab experiments. It is expected that by 2010, sequencing of individual genomes will be affordable generating an unprecedented increase of life sciences data, in the form of sequences, expressions, networks, images, literature. Pattern recognition techniques lie at the heart of discovery of new insights into biological knowledge, as the presence of particular patterns or structure is often an indication of its function. The aim of the workshop series Pattern Recognition in Bioinformatics (PRIB) is to bring pattern recognition scientists and life scientists together to promote pattern recognition applications to solve life sciences problems. This volume presents the proceedings of the 2nd IAPR Workshop PRIB 2007 held in Singapore, October 1–2, 2007. It includes 38 technical contributions that were selected by the International Program Committee from 125 submissions. Each of these rigorously reviewed papers was presented orally at the workshop. The proceedings consists of six parts. Part 1: Sequence Analysis; Part 2: Prediction of Protein Structure, Interaction, and Localization; Part 3: Gene Expression Analysis; Part 4: Pathway Analysis; Part 5: Medical Informatics; and Part 6: Bioimaging.

• Clustal
• Computer
• Fuzzy
• Gene Ontology
• Mutation
• algorithms
• association rule mining
• bioinformatics
• biomedical informatics
• classification
• clustering
• data mining
• gene expression
• genes
• knowledge discovery

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