Pattern Recognition in Bioinformatics

7th IAPR International Conference, PRIB 2012, Tokyo, Japan, November 8-10, 2012. Proceedings

Editors:

ISBN: 978-3-642-34122-9 (Print) 978-3-642-34123-6 (Online)

Table of contents (24 chapters)

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  1. Front Matter

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  2. Generic Methods – I

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      Pages 1-13

      Robust Community Detection Methods with Resolution Parameter for Complex Detection in Protein Protein Interaction Networks

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      Pages 14-25

      Machine Learning Scoring Functions Based on Random Forest and Support Vector Regression

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      Pages 26-37

      A Genetic Algorithm for Scale-Based Translocon Simulation

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      Pages 38-48

      A Framework of Gene Subset Selection Using Multiobjective Evolutionary Algorithm

  3. Generic Methods – II

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      Pages 49-58

      Multiple Tree Alignment with Weights Applied to Carbohydrates to Extract Binding Recognition Patterns

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      Pages 59-70

      A Unified Adaptive Co-identification Framework for High-D Expression Data

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      Pages 71-81

      Protein Clustering on a Grassmann Manifold

  4. Visualization, Image Analysis, and Platforms

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      Pages 82-93

      Improving the Portability and Performance of jViz.RNA – A Dynamic RNA Visualization Software

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      Pages 94-105

      A Novel Machine Learning Approach for Detecting the Brain Abnormalities from MRI Structural Images

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      Pages 106-117

      An Open Framework for Extensible Multi-stage Bioinformatics Software

  5. Applications of Pattern Recognition Techniques

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      Pages 118-128

      An Algorithm to Assemble Gene-Protein-Reaction Associations for Genome-Scale Metabolic Model Reconstruction

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      Pages 129-140

      A Machine Learning and Chemometrics Assisted Interpretation of Spectroscopic Data – A NMR-Based Metabolomics Platform for the Assessment of Brazilian Propolis

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      Pages 141-152

      Principal Component Analysis for Bacterial Proteomic Analysis

  6. Protein Structure and Docking

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      Pages 153-165

      Application of the Multi-modal Relevance Vector Machine to the Problem of Protein Secondary Structure Prediction

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      Pages 166-177

      Cascading Discriminant and Generative Models for Protein Secondary Structure Prediction

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      Pages 178-187

      Improvement of the Protein–Protein Docking Prediction by Introducing a Simple Hydrophobic Interaction Model: An Application to Interaction Pathway Analysis

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      Pages 188-197

      Representation of Protein Secondary Structure Using Bond-Orientational Order Parameters

  7. Complex Data Analysis

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      Pages 198-209

      Diagnose the Premalignant Pancreatic Cancer Using High Dimensional Linear Machine

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      Pages 210-221

      Predicting V(D)J Recombination Using Conditional Random Fields

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      Pages 222-232

      A Simple Genetic Algorithm for Biomarker Mining

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