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Pattern Recognition in Bioinformatics

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

  • Conference proceedings
  • © 2012

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Editors:
  1. Tetsuo Shibuya

    1. Institute of Medical Science, University of Tokyo, Minato-ku, Japan

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  2. Hisashi Kashima

    1. Department of Mathematical Informatics, The University of Tokyo, Bunkyo-ku, Japan

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  3. Jun Sese

    1. Department of Comouter Science, Tokyo Institute of Technology, Meguro-ku, Japan

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  4. Shandar Ahmad

    1. Bioinformatics Project, National Institute of Biomedical Innovation, Suita, Japan

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 7632)

Part of the book sub series: Lecture Notes in Bioinformatics (LNBI)

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Conference proceedings info: PRIB 2012.

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About this book

This book constitutes the refereed proceedings of the 7th International Conference on Pattern Recognition in Bioinformatics, PRIB 2012, held in Tokyo, Japan, in November 2012. The 24 revised full papers presented were carefully reviewed and selected from 33 submissions. Their topics are widely ranging from fundamental techniques, sequence analysis to biological network analysis. The papers are organized in topical sections on generic methods, visualization, image analysis, and platforms, applications of pattern recognition techniques, protein structure and docking, complex data analysis, and sequence analysis.

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Table of contents (24 papers)

  1. Front Matter

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  3. Generic Methods – II

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

      • Masae Hosoda, Yukie Akune, Kiyoko F. Aoki-Kinoshita
      Pages 49-58

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

      • Shuzhong Zhang, Kun Wang, Cody Ashby, Bilian Chen, Xiuzhen Huang
      Pages 59-70

    3. Protein Clustering on a Grassmann Manifold

      • Chendra Hadi Suryanto, Hiroto Saigo, Kazuhiro Fukui
      Pages 71-81

  4. Visualization, Image Analysis, and Platforms

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

      • Boris Shabash, Kay Wiese, Edward Glen
      Pages 82-93

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

      • Lavneet Singh, Girija Chetty, Dharmendra Sharma
      Pages 94-105

    3. An Open Framework for Extensible Multi-stage Bioinformatics Software

      • Gabriel Keeble-Gagnère, Johan Nyström-Persson, Matthew I. Bellgard, Kenji Mizuguchi
      Pages 106-117

  5. Applications of Pattern Recognition Techniques

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

      • João Cardoso, Paulo Vilaça, Simão Soares, Miguel Rocha
      Pages 118-128

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

      • Marcelo Maraschin, Amélia Somensi-Zeggio, Simone K. Oliveira, Shirley Kuhnen, Maíra M. Tomazzoli, Ana C. M. Zeri et al.
      Pages 129-140

    3. Principal Component Analysis for Bacterial Proteomic Analysis

      • Y. -h. Taguchi, Akira Okamoto
      Pages 141-152

  6. Protein Structure and Docking

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

      • Nikolay Razin, Dmitry Sungurov, Vadim Mottl, Ivan Torshin, Valentina Sulimova, Oleg Seredin et al.
      Pages 153-165

    2. Cascading Discriminant and Generative Models for Protein Secondary Structure Prediction

      • Fabienne Thomarat, Fabien Lauer, Yann Guermeur
      Pages 166-177

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

      • Masahito Ohue, Yuri Matsuzaki, Takashi Ishida, Yutaka Akiyama
      Pages 178-187

    4. Representation of Protein Secondary Structure Using Bond-Orientational Order Parameters

      • Cem Meydan, Osman Ugur Sezerman
      Pages 188-197

  7. Complex Data Analysis

    1. Diagnose the Premalignant Pancreatic Cancer Using High Dimensional Linear Machine

      • Yifeng Li, Alioune Ngom
      Pages 198-209

    2. Predicting V(D)J Recombination Using Conditional Random Fields

      • Raunaq Malhotra, Shruthi Prabhakara, Raj Acharya
      Pages 210-221
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Other volumes

  1. Pattern Recognition in Bioinformatics

Editors and Affiliations

  • Institute of Medical Science, University of Tokyo, Minato-ku, Japan

    Tetsuo Shibuya

  • Department of Mathematical Informatics, The University of Tokyo, Bunkyo-ku, Japan

    Hisashi Kashima

  • Department of Comouter Science, Tokyo Institute of Technology, Meguro-ku, Japan

    Jun Sese

  • Bioinformatics Project, National Institute of Biomedical Innovation, Suita, Japan

    Shandar Ahmad

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