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Distributed and Sequential Algorithms for Bioinformatics and Computational Biology

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Published in Distributed And Sequential Algorithms For Bioinformatics (Computational Biology 23)

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Harnessing the Power of Algorithms for Biological Data Analysis and Discovery

In the era of big data and computational biology, efficient algorithms have become indispensable tools for analyzing and interpreting the vast amount of biological data available. Distributed and Sequential Algorithms for Bioinformatics and Computational Biology provides a comprehensive overview of the latest algorithmic techniques specifically designed for bioinformatics and computational biology applications.

Key Features

Authoritative Authors: Written by leading experts in the field, this book presents state-of-the-art algorithms and their practical applications in bioinformatics.
Comprehensive Coverage: Covers a wide range of topics, including sequence alignment, phylogenetics, genome assembly, gene regulation, and protein-protein interactions.
Practical Applications: Demonstrates how algorithms can be applied to solve real-world problems in bioinformatics and computational biology.
Real-World Examples: Includes case studies and examples to illustrate the practical implementation of algorithms in biological research.
Accessible Presentation: Written in a clear and concise style, making it accessible to both students and researchers.

Chapter Outline

Distributed and Sequential Algorithms for Bioinformatics (Computational Biology 23)

Distributed and Sequential Algorithms for Bioinformatics (Computational Biology Book 23)

by Christoffer Petersen

4.5 out of 5

Language	:	English
File size	:	12730 KB
Text-to-Speech	:	Enabled
Screen Reader	:	Supported
Enhanced typesetting	:	Enabled
Word Wise	:	Enabled
Print length	:	586 pages

Chapter 1: ** to Bioinformatics and Computational Biology**

Overview of the field and its computational challenges

Chapter 2:Sequence Alignment Algorithms

Dynamic programming algorithms (Smith-Waterman, Needleman-Wunsch)
Heuristic algorithms (BLAST, FASTA)
Alignment visualization and statistical significance

Chapter 3:Phylogenetic Tree Construction

Distance-based methods (NJ, UPGMA, Neighbor-Joining)
Character-based methods (Parsimony, Maximum Likelihood)
Phylogenetic tree viewing and editing

Chapter 4:Genome Assembly Algorithms

De Bruijn graph construction
Overlap-layout-consensus methods
Hybrid assembly approaches

Chapter 5:Gene Regulation Algorithms

RNA-seq data analysis
ChIP-seq data analysis
Motif finding and transcription factor binding site prediction

Chapter 6:Protein-Protein Interaction Prediction

Protein sequence analysis
Protein structure prediction
Docking and binding site prediction

Chapter 7:Distributed Algorithms for Bioinformatics

Parallel sequence alignment
Phylogenetic tree construction
Genome assembly
Gene regulation analysis

Chapter 8:Applications and Case Studies

DNA barcoding for species identification
Drug discovery using molecular dynamics simulations
Single-cell RNA sequencing for developmental biology

Distributed and Sequential Algorithms for Bioinformatics and Computational Biology is a valuable resource for graduate students, researchers, and professionals in the fields of bioinformatics, computational biology, and data science. With its comprehensive coverage, practical examples, and accessible presentation, this book provides a solid foundation for understanding and applying algorithms to solve challenging biological problems.

Target Audience

Graduate students and researchers in bioinformatics and computational biology
Computational scientists and data analysts interested in biological data
Biologists and medical professionals seeking to leverage computational tools
Software developers working on bioinformatics applications

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Distributed and Sequential Algorithms for Bioinformatics (Computational Biology Book 23)

by Christoffer Petersen

4.5 out of 5