Data Mining Techniques for the Life Sciences / Edition 1

Data Mining Techniques for the Life Sciences / Edition 1

ISBN-10:
1603272402
ISBN-13:
9781603272407
Pub. Date:
12/14/2009
Publisher:
Springer-Verlag New York, LLC
ISBN-10:
1603272402
ISBN-13:
9781603272407
Pub. Date:
12/14/2009
Publisher:
Springer-Verlag New York, LLC
Data Mining Techniques for the Life Sciences / Edition 1

Data Mining Techniques for the Life Sciences / Edition 1

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Overview

Most life science researchers will agree that biology is not a truly theoretical branch of science. The hype around computational biology and bioinformatics beginning in the nineties of the 20th century was to be short lived (1, 2). When almost no value of practical importance such as the optimal dose of a drug or the three-dimensional structure of an orphan protein can be computed from fundamental principles, it is still more straightforward to determine them experimentally. Thus, experiments and observations do generate the overwhelming part of insights intobiology and medicine. The extrapolation depth and the prediction power of the theoretical argument in life sciences still have a long way to go. Yet, two trends have qualitatively changed the way how biological research is done today. The number of researchers has dramatically grown and they, armed with the same prools, have produced lots of similarly structured data. Finally, high-throu- put technologies such as DNA sequencing or array-based expression profiling have been around for just a decade. Nevertheless, with their high level of uniform data generation, they reach the threshold of totally describing a living organism at the biomolecular level for the first time in human history. Whereas getting exact data about living systems and the sophistication of experimental procedures have primarily absorbed the minds of researchers previously, the weight increasingly shifts to the problem of interpreting accumulated data in terms of biological function and bio- lecular mechanisms.

Product Details

ISBN-13: 9781603272407
Publisher: Springer-Verlag New York, LLC
Publication date: 12/14/2009
Series: Methods in Molecular Biology , #609
Edition description: 2010
Pages: 407
Product dimensions: 7.20(w) x 10.10(h) x 1.30(d)

Table of Contents

Databases.- Nucleic Acid Sequence and Structure Databases.- Genomic Databases and Resources at the National Center for Biotechnology Information.- Protein Sequence Databases.- Protein Structure Databases.- Protein Domain Architectures.- Thermodynamic Database for Proteins: Features and Applications.- Enzyme Databases.- Biomolecular Pathway Databases.- Databases of Protein–Protein Interactions and Complexes.- Data Mining Techniques.- Proximity Measures for Cluster Analysis.- Clustering Criteria and Algorithms.- Neural Networks.- A User’s Guide to Support Vector Machines.- Hidden Markov Models in Biology.- Database Annotations and Predictions.- Integrated Tools for Biomolecular Sequence-Based Function Prediction as Exemplified by the ANNOTATOR Software Environment.- Computational Methods for Ab Initio and Comparative Gene Finding.- Sequence and Structure Analysis of Noncoding RNAs.- Conformational Disorder.- Protein Secondary Structure Prediction.- Analysis and Prediction of Protein Quaternary Structure.- Prediction of Posttranslational Modification of Proteins from Their Amino Acid Sequence.- Protein Crystallizability.
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