Authors:
- Contributors examine how sequence analysis becomes even more powerful if it is combined with automated scientific text mining (for the prediction of gene function and gene-disease association), with the analysis of expression data or allele occurrences (single-nucleotide polymorphisms) and frequencies
- Summarizes non-trivial theoretical predictions for regulatory and metabolic networks that have received experimental confirmation
- Includes supplementary material: sn.pub/extras
Part of the book series: Molecular Biology Intelligence Unit (MBIU)
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Table of contents (12 chapters)
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Front Matter
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Prediction of Post-translational modifications from amino acid sequence: Problems, pitfalls, methodological hints
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Deriving Biological Function of Genome Information with Biomolecular Sequence and Structure Analysis
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Front Matter
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Complementing Biomolecular Sequence Analysis with Text Mining in Scientific Articles
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Front Matter
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Mechanistic Predictions from the Analysis of Biomolecular Networks
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Front Matter
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Mechanistic Predictions from the Analysis of Biomolecular Sequence Populations: Considering Evolution for Function Prediction
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Front Matter
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Back Matter
About this book
In this anthology, leading researchers present critical reviews of methods and high-impact applications in computational biology that lead to results that also non-bioinformaticians must know to design efficient experimental research plans. Discovering Biomolecular Mechanisms with Computational Biology also summarizes non-trivial theoretical predictions for regulatory and metabolic networks that have received experimental confirmation.
Discovering Biomolecular Mechanisms with Computational Biology is essential reading for life science researchers and higher-level students that work on biomolecular mechanisms and wish to understand the impact of computational biology for their success.
Authors and Affiliations
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Bioinformatics Group, Institute of Molecular Pathology, Vienna, Austria
Frank Eisenhaber
Bibliographic Information
Book Title: Discovering Biomolecular Mechanisms with Computational Biology
Authors: Frank Eisenhaber
Series Title: Molecular Biology Intelligence Unit
DOI: https://doi.org/10.1007/0-387-36747-0
Publisher: Springer New York, NY
eBook Packages: Biomedical and Life Sciences, Biomedical and Life Sciences (R0)
Copyright Information: Springer-Verlag US 2006
Hardcover ISBN: 978-0-387-34527-7Published: 13 June 2006
Softcover ISBN: 978-1-4419-4177-0Published: 19 November 2010
eBook ISBN: 978-0-387-36747-7Published: 20 March 2007
Series ISSN: 1431-0414
Edition Number: 1
Number of Pages: XI, 147
Number of Illustrations: 41 b/w illustrations, 1 illustrations in colour
Additional Information: Jointly published with Landes Bioscience, Austin, TX, USA
Topics: Biochemistry, general, Biomedicine general, Molecular Medicine, Medical Microbiology