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Pattern Recognition in Bioinformatics Lecture Notes in Bioinformatics

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Pattern Recognition in Bioinformatics Lecture Notes in Bioinformatics Synopsis

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.

About This Edition

ISBN: 9783540752851
Publication date:
Author: Jagath C Rajapakse, Bertil Schmidt, Gwenn Volkert
Publisher: Springer an imprint of Springer Berlin Heidelberg
Format: Paperback
Pagination: 410 pages
Series: Lecture Notes in Computer Science
Genres: Biochemistry
Computational biology / bioinformatics
Maths for computer scientists
Expert systems / knowledge-based systems
Data mining
Artificial intelligence
Probability and statistics
Databases