Introduction To Computational Molecular Biology
Download Introduction To Computational Molecular Biology PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Introduction To Computational Molecular Biology book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Introduction to Computational Molecular Biology
Author: João Carlos Setubal
language: en
Publisher: Pws Publishing Company
Release Date: 1997
Basic concepts of molecular biology. Strings, graphs, and algorithms. Sequence comparasion and database search. Fragment assembly of DNA. Physical mapping of DNA. Phylogenetic trees. Genome rearrangements. Molecular structure prediction. epilogue: computing with DNA. Answers to selected exercises. References. index.
Introduction to Computational Biology
Author: Bernhard Haubold
language: en
Publisher: Springer Science & Business Media
Release Date: 2006-08-09
Written with the advanced undergraduate in mind, this book introduces into the field of Bioinformatics. The authors explain the computational and conceptional background to the analysis of large-scale sequence data. Many of the corresponding analysis methods are rooted in evolutionary thinking, which serves as a common thread throughout the book. The focus is on methods of comparative genomics and subjects covered include: alignments, gene finding, phylogeny, and the analysis of single nucleotide polymorphisms (SNPs). The volume contains exercises, questions & answers to selected problems.
Computational Molecular Biology
Recently molecular biology has undergone unprecedented development generating vast quantities of data needing sophisticated computational methods for analysis, processing and archiving. This requirement has given birth to the truly interdisciplinary field of computational biology, or bioinformatics, a subject reliant on both theoretical and practical contributions from statistics, mathematics, computer science and biology. * Provides the background mathematics required to understand why certain algorithms work * Guides the reader through probability theory, entropy and combinatorial optimization * In-depth coverage of molecular biology and protein structure prediction * Includes several less familiar algorithms such as DNA segmentation, quartet puzzling and DNA strand separation prediction * Includes class tested exercises useful for self-study * Source code of programs available on a Web site Primarily aimed at advanced undergraduate and graduate students from bioinformatics, computer science, statistics, mathematics and the biological sciences, this text will also interest researchers from these fields.