Fundamentals Of Bioinformatics And Computational Biology_ Methods And Exercises In MATLAB-Springer (2015)

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Fundamentals of Bioinformatics and Computational Biology_ Methods and Exercises in MATLAB-Springer <span style=color:#777>(2015)</span>

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Fundamentals of Bioinformatics and Computational Biology - Methods and Exercises in MATLAB

by Singh, Gautam B.

# Publisher: Springer International (2015)
# Series: Modeling and Optimization in Science and Technologies, Vol. 6
# Language: English
# Pages: 339 pages
# Print ISBN: 9783319114026

Description

• Clearly presents core bioinformatics principles with “hands-on” example

• Illustrates the use of MATLAB bioinformatics toolbox™ for solving complex bioinformatics problems

• Synthetizes concepts in databases, machine learning, statistics and visualization for bioinformatics research

• Mainly written for computer scientists and engineers

This book offers comprehensive coverage of all the core topics of bioinformatics, and includes practical examples completed using the MATLAB bioinformatics toolbox™. It is primarily intended as a textbook for engineering and computer science students attending advanced undergraduate and graduate courses in bioinformatics and computational biology. The book develops bioinformatics concepts from the ground up, starting with an introductory chapter on molecular biology and genetics. This chapter will enable physical science students to fully understand and appreciate the ultimate goals of applying the principles of information technology to challenges in biological data management, sequence analysis, and systems biology. The first part of the book also includes a survey of existing biological databases, tools that have become essential in today’s biotechnology research.

The second part of the book covers methodologies for retrieving biological information, including fundamental algorithms for sequence comparison, scoring, and determining evolutionary distance. The main focus of the third part is on modeling biological sequences and patterns as Markov chains. It presents key principles for analyzing and searching for sequences of significant motifs and biomarkers. The last part of the book, dedicated to systems biology, covers phylogenetic analysis and evolutionary tree computations, as well as gene expression analysis with microarrays. In brief, the book offers the ideal hands-on reference guide to the field of bioinformatics and computational biology.

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