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Artificial Intelligence Technologies for Computational Biology

By: Amrit Lal Sangal (Edited by) , Ranjeet Kumar Rout (Edited by) , Sabha Sheikh (Edited by) , Saiyed Umer (Edited by)

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Ksh 30,400.00

Format: Hardback or Cased Book

ISBN-10: 1032160004

ISBN-13: 9781032160009

Publisher: Taylor & Francis Ltd

Imprint: CRC Press

Country of Manufacture: GB

Country of Publication: GB

Publication Date: Nov 10th, 2022

Publication Status: Active

Product extent: 324 Pages

Weight: 644.00 grams

Dimensions (height x width x thickness): 16.20 x 24.10 x 2.60 cms

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This text emphasizes the importance of artificial intelligence techniques in the field of biological computation. It also discusses fundamental principles that can be applied beyond bio-inspired computing.

This text emphasizes the importance of artificial intelligence techniques in the field of biological computation. It also discusses fundamental principles that can be applied beyond bio-inspired computing.

It comprehensively covers important topics including data integration, data mining, machine learning, genetic algorithms, evolutionary computation, evolved neural networks, nature-inspired algorithms, and protein structure alignment. The text covers the application of evolutionary computations for fractal visualization of sequence data, artificial intelligence, and automatic image interpretation in modern biological systems.

The text is primarily written for graduate students and academic researchers in areas of electrical engineering, electronics engineering, computer engineering, and computational biology.

This book:

• Covers algorithms in the fields of artificial intelligence, and machine learning useful in biological data analysis.

• Discusses comprehensively artificial intelligence and automatic image interpretation in modern biological systems.

• Presents the application of evolutionary computations for fractal visualization of sequence data.

• Explores the use of genetic algorithms for pair-wise and multiple sequence alignments.

• Examines the roles of efficient computational techniques in biology.


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