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Yanqing Zhang, Jagath C. Rajapakse, "Machine Learning in Bioinformatics (Wiley Series in Bioinformatics)"

An introduction to machine learning methods and their applications to problems in bioinformatics

Machine learning techniques are increasingly being used to address problems in computational biology and bioinformatics. Novel computational techniques to analyze high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. Machine learning techniques such as Markov models, support vector machines, neural networks, and graphical models have been successful in analyzing life science data because of their capabilities in handling randomness and uncertainty of data noise and in generalization.

From an internationally recognized panel of prominent researchers in the field, Machine Learning in Bioinformatics compiles recent approaches in machine learning methods and their applications in addressing contemporary problems in bioinformatics. Coverage includes: feature selection for genomic and proteomic data mining; comparing variable selection methods in gene selection and classification of microarray data; fuzzy gene mining; sequence-based prediction of residue-level properties in proteins; probabilistic methods for long-range features in biosequences; and much more.

Machine Learning in Bioinformatics is an indispensable resource for computer scientists, engineers, biologists, mathematicians, researchers, clinicians, physicians, and medical informaticists. It is also a valuable reference text for computer science, engineering, and biology courses at the upper undergraduate and graduate levels.

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	EBook Torrents Baldi P., Brunak S. Bioinformatics.. the machine learning approa
	Science/Engineering Knowledge Discovery in Bioinformatics: Techniques, Methods, and Applications (Wiley Series in Bioinformatics) Publisher: WileyLanguage: englishISBN: 047177796XPaperback: 363 pagesData: June 22, 2007Format: PDFDescription: The purpose of this edited book is to bring together the ideas and findings of data mining researchers and bioinformaticians by ...
	Study Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics Clara Pizzuti, Marylyn D. Ritchie, Mario Giacobini, "Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics: 7th European Conference, EvoBIO 2009 Tübingen, Germany, April 15-17, 2009 ... Computer Science and General ...
	Science/Engineering Grid Computing for Bioinformatics and Computational Biology (Wiley Series in Bioinformatics) Grid Computing for Bioinformatics and Computational Biology (Wiley Series in Bioinformatics)Wiley-Interscience \| ISBN: 0471784095 \| 2007-12-17 \| PDF \| 392 pages \| 5 Mb Bioinformatics is fast emerging as an important discipline for academic ...
	Technical Applications of Fuzzy Logic in Bioinformatics (Series on Advances in Bioinformatics and Computational Biology) ISBN: 1848162588 Publisher: Imperial College Press Author: Dong Xu, James M. Keller, Mihail Popescu, Rajkumar BondugulaDescription:Many biological systems and objects are intrinsically fuzzy as their properties and behaviors contain randomn ...
	Bioinformatics: The Machine Learning Approach, 2nd Edition Pierre Baldi, Søren Brunak, «Bioinformatics: The Machine Learning Approach, 2nd Edition»The MIT Press \| ISBN 026202506X \| 2001 Year \| PDF \| 5,94 Mb \| 400 Pages"An unprecedented wealth of data is being generated by genome sequencing proje ...

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