SEQUENCE COMPARISON: THEORY AND METHODS (COMPUTATIONAL BIOLOGY) BY KUN-MAO CHAO, LOUXIN ZHANG

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SEQUENCE COMPARISON: THEORY AND METHODS (COMPUTATIONAL BIOLOGY) BY KUN-MAO CHAO, LOUXIN ZHANG PDF

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From the Back Cover Biomolecular sequence comparison is the origin of bioinformatics. Today, powerful sequence comparison methods, together with comprehensive biological databases, have changed the practice of molecular biology and genomics. This in-depth, state-of-the-art study of sequence alignment and homology search, covers the full spectrum of the field - from alignment methods to the theory of scoring matrices and alignment score statistics. Following a comprehensive introduction, this useful text/reference focuses on algorithms and techniques, as well as discusses the theory. This easy-to-follow text examines alignment methods and techniques, features a new issue of sequence comparison (the spacedseed technique), addresses several new flexible strategies for coping with various scoring schemes, and covers the theory on the significance of high-scoring segment pairs between two unalignment sequences. Useful appendices are provided for basic concepts in molecular biology, primer in statistics and software for sequence alignment. The book is written for readers with little or no knowledge of biology, algorithms and probability. Features: • Presents a rigorous yet reader-friendly text on the algorithmic techniques and mathematical foundations of sequence alignment and homology search • Offers a tutorial to aid all levels of readers • Covers the basic algorithms and methods for sequence alignment • Introduces popular homology search programs

• Familiarizes readers with multiple sequence alignment • Deals with the Karlin-Altschul statistics of optimal local alignment scores • Discusses substitution matrices • Provides end-of-chapter bibliographic notes and further reading suggestions that report related work and recent progresses Based on lectures given to students studying bioinformatics and mathematics, this state-of-the-art study of sequence alignment and homology search is an ideal resource and toolkit for undergraduates and will appeal to biologists who wish to know how to use homology search tools more intelligently.

SEQUENCE COMPARISON: THEORY AND METHODS (COMPUTATIONAL BIOLOGY) BY KUN-MAO CHAO, LOUXIN ZHANG PDF

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SEQUENCE COMPARISON: THEORY AND METHODS (COMPUTATIONAL BIOLOGY) BY KUN-MAO CHAO, LOUXIN ZHANG PDF

Biomolecular sequence comparison is the origin of bioinformatics. This book gives a complete indepth treatment of the study of sequence comparison. The book examines alignment methods and techniques, and features a new issue of sequence comparison.

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Sales Rank: #5614291 in Books Published on: 2010-10-22 Released on: 2010-10-22 Original language: English Number of items: 1 Dimensions: 9.25" h x .53" w x 6.10" l, .73 pounds Binding: Paperback 209 pages

From the Back Cover Biomolecular sequence comparison is the origin of bioinformatics. Today, powerful sequence comparison methods, together with comprehensive biological databases, have changed the practice of molecular biology and genomics. This in-depth, state-of-the-art study of sequence alignment and homology search, covers the full spectrum of the field - from alignment methods to the theory of scoring matrices and alignment score statistics. Following a comprehensive introduction, this useful text/reference focuses on algorithms and techniques, as well as discusses the theory. This easy-to-follow text examines alignment methods and techniques, features a new issue of sequence comparison (the spacedseed technique), addresses several new flexible strategies for coping with various scoring schemes, and covers the theory on the significance of high-scoring segment pairs between two unalignment sequences. Useful appendices are provided for basic concepts in molecular biology, primer in statistics and software for sequence alignment. The book is written for readers with little or no knowledge of biology, algorithms and probability. Features: • Presents a rigorous yet reader-friendly text on the algorithmic techniques and mathematical foundations of sequence alignment and homology search • Offers a tutorial to aid all levels of readers • Covers the basic algorithms and methods for sequence alignment

• Introduces popular homology search programs • Familiarizes readers with multiple sequence alignment • Deals with the Karlin-Altschul statistics of optimal local alignment scores • Discusses substitution matrices • Provides end-of-chapter bibliographic notes and further reading suggestions that report related work and recent progresses Based on lectures given to students studying bioinformatics and mathematics, this state-of-the-art study of sequence alignment and homology search is an ideal resource and toolkit for undergraduates and will appeal to biologists who wish to know how to use homology search tools more intelligently.

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SEQUENCE COMPARISON: THEORY AND METHODS (COMPUTATIONAL BIOLOGY) BY KUN-MAO CHAO, LOUXIN ZHANG PDF

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• Discusses substitution matrices • Provides end-of-chapter bibliographic notes and further reading suggestions that report related work and recent progresses Based on lectures given to students studying bioinformatics and mathematics, this state-of-the-art study of sequence alignment and homology search is an ideal resource and toolkit for undergraduates and will appeal to biologists who wish to know how to use homology search tools more intelligently.

Curious? Naturally, this is why, we expect you to click the link page to see, and afterwards you can enjoy guide Sequence Comparison: Theory And Methods (Computational Biology) By Kun-Mao Chao, Louxin Zhang downloaded and install up until finished. You could save the soft file of this Sequence Comparison: Theory And Methods (Computational Biology) By Kun-Mao Chao, Louxin Zhang in your gadget. Certainly, you will bring the gadget almost everywhere, won't you? This is why, every time you have downtime, every time you could enjoy reading by soft duplicate book Sequence Comparison: Theory And Methods (Computational Biology) By Kun-Mao Chao, Louxin Zhang

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