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Data mining for bioinformatics

Dua, Sumeet - Personal Name; Pradeep Chowriappa - Personal Name;

Covering theory, algorithms, and methodologies, as well as data mining technologies, Data Mining for Bioinformatics provides a comprehensive discussion of data-intensive computations used in data mining with applications in bioinformatics. It supplies a broad, yet in-depth, overview of the application domains of data mining for bioinformatics to help readers from both biology and computer science backgrounds gain an enhanced understanding of this cross-disciplinary field.

The book offers authoritative coverage of data mining techniques, technologies, and frameworks used for storing, analyzing, and extracting knowledge from large databases in the bioinformatics domains, including genomics and proteomics. It begins by describing the evolution of bioinformatics and highlighting the challenges that can be addressed using data mining techniques. Introducing the various data mining techniques that can be employed in biological databases, the text is organized into four sections:

Supplies a complete overview of the evolution of the field and its intersection with computational learning
Describes the role of data mining in analyzing large biological databases—explaining the breath of the various feature selection and feature extraction techniques that data mining has to offer
Focuses on concepts of unsupervised learning using clustering techniques and its application to large biological data
Covers supervised learning using classification techniques most commonly used in bioinformatics—addressing the need for validation and benchmarking of inferences derived using either clustering or classification
The book describes the various biological databases prominently referred to in bioinformatics and includes a detailed list of the applications of advanced clustering algorithms used in bioinformatics. Highlighting the challenges encountered during the application of classification on biological databases, it considers systems of both single and ensemble classifiers and shares effort-saving tips for model selection and performance estimation strategies.


Availability
#
4th Floor-i3L Library 572.330285 Dua d
20150100348
Available
#
Tandon / Reserved Collection 572.330285 Dua d
20150100347
Available
#
4th Floor-i3L Library 572.330285 Dua d
20150100346
Available
Detail Information
Series Title
-
Call Number
572.330285 Dua d
Publisher
Boca Raton, FL : CRC Press., 2013
Collation
xix, 328 p. : ill. : ind. ; 24 cm
Language
English
ISBN/ISSN
9780849328015
Classification
NONE
Content Type
-
Media Type
-
Carrier Type
-
Edition
-
Subject(s)
Bioinformatics
Data mining.
Specific Detail Info
-
Statement of Responsibility
-
Other version/related

No other version available

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Indonesia International Institute for Life Sciences - Learning Resources Center
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i3L Learning Resources Center (LRC) is vital part of your academic experience at Indonesia International Institute for Life-Sciences. LRC exists to support the teaching, learning and research programs of the Institute through the provision of high quality services and facilities which include access to a range of printed and digital resources primarily in the field of life-sciences and business. 

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