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Pattern Recognition in Bioinformatics

International Workshop, PRIB 2006, Hong Kong, China, August 20, 2006, Proceedings

  • Conference proceedings
  • © 2006

Overview

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 4146)

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

Included in the following conference series:

Conference proceedings info: PRIB 2006.

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Table of contents (19 papers)

  1. Pattern Recognition in Bioinformatics: An Introduction

  2. Part 1: Signal and Motif Detection; Gene Selection

  3. Part 2: Models of DNA, RNA, and Protein Structures

  4. Part 3: Biological Databases and Imaging

Other volumes

  1. Pattern Recognition in Bioinformatics

Keywords

About this book

The field of bioinformatics has two main objectives: the creation and maintenance of biological databases, and the discovery of knowledge from life sciences data in order to unravel the mysteries of biological function, leading to new drugs and therapies for human disease. Life sciences data come in the form of biological sequences, structures, pathways, or literature. One major aspect of discovering biological knowledge is to search, predict, or model specific patterns of a given dataset, which have some relevance to an important biological phenomenon or another dataset. To date, many pattern recognition algorithms have been applied or catered to address a wide range of bioinformatics problems. The 2006 Workshop of Bioinformatics in Pattern Recognition (PRIB 2006) marks the beginning of a series of workshops that is aimed at gathering researchers applying pattern recognition algorithms in an attempt to resolve problems in computational biology and bioinformatics. This volume presentsthe proceedings of Workshop PRIB 2006 held in Hong Kong, China, on August 20, 2006. It includes 19 technical contributions that were selected by the Program Committee from 43 submissions. We give a brief introduction to pattern recognition in bioinformatics in the first paper. The rest of the volume consists of three parts. Part 1: signal and motif detection, and gene selection. Part 2: models of DNA, RNA, and protein structures. Part 3: biological databases and imaging.

Editors and Affiliations

  • Singapore-MIT Alliance, Singapore

    Jagath C. Rajapakse

  • School of Computing, National University of Singapore, Singapore

    Limsoon Wong

  • Computer Science and Engineering, The Penn State University, USA

    Raj Acharya

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