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Introduction to Computational Molecular Biology by João Carlos Setubal,João Meidanis Pdf
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 by Bernhard Haubold,Thomas Wiehe Pdf
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 by Peter Clote,Rolf Backofen Pdf
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 bioniformatics, computer science, statistics, mathematics and the biological sciences, this text will also interest researchers from these fields.
Introduction to Computational Biology by Michael S. Waterman Pdf
Biology is in the midst of a era yielding many significant discoveries and promising many more. Unique to this era is the exponential growth in the size of information-packed databases. Inspired by a pressing need to analyze that data, Introduction to Computational Biology explores a new area of expertise that emerged from this fertile field- the combination of biological and information sciences. This introduction describes the mathematical structure of biological data, especially from sequences and chromosomes. After a brief survey of molecular biology, it studies restriction maps of DNA, rough landmark maps of the underlying sequences, and clones and clone maps. It examines problems associated with reading DNA sequences and comparing sequences to finding common patterns. The author then considers that statistics of pattern counts in sequences, RNA secondary structure, and the inference of evolutionary history of related sequences. Introduction to Computational Biology exposes the reader to the fascinating structure of biological data and explains how to treat related combinatorial and statistical problems. Written to describe mathematical formulation and development, this book helps set the stage for even more, truly interdisciplinary work in biology.
Handbook of Computational Molecular Biology by Srinivas Aluru Pdf
The enormous complexity of biological systems at the molecular level must be answered with powerful computational methods. Computational biology is a young field, but has seen rapid growth and advancement over the past few decades. Surveying the progress made in this multidisciplinary field, the Handbook of Computational Molecular Biology of
Pattern Recognition in Computational Molecular Biology by Mourad Elloumi,Costas Iliopoulos,Jason T. L. Wang,Albert Y. Zomaya Pdf
A comprehensive overview of high-performance pattern recognition techniques and approaches to Computational Molecular Biology This book surveys the developments of techniques and approaches on pattern recognition related to Computational Molecular Biology. Providing a broad coverage of the field, the authors cover fundamental and technical information on these techniques and approaches, as well as discussing their related problems. The text consists of twenty nine chapters, organized into seven parts: Pattern Recognition in Sequences, Pattern Recognition in Secondary Structures, Pattern Recognition in Tertiary Structures, Pattern Recognition in Quaternary Structures, Pattern Recognition in Microarrays, Pattern Recognition in Phylogenetic Trees, and Pattern Recognition in Biological Networks. Surveys the development of techniques and approaches on pattern recognition in biomolecular data Discusses pattern recognition in primary, secondary, tertiary and quaternary structures, as well as microarrays, phylogenetic trees and biological networks Includes case studies and examples to further illustrate the concepts discussed in the book Pattern Recognition in Computational Molecular Biology: Techniques and Approaches is a reference for practitioners and professional researches in Computer Science, Life Science, and Mathematics. This book also serves as a supplementary reading for graduate students and young researches interested in Computational Molecular Biology.
Introduction to Computational Biology by Michael S. Waterman Pdf
Biology is in the midst of a era yielding many significant discoveries and promising many more. Unique to this era is the exponential growth in the size of information-packed databases. Inspired by a pressing need to analyze that data, Introduction to Computational Biology explores a new area of expertise that emerged from this fertile field- the combination of biological and information sciences. This introduction describes the mathematical structure of biological data, especially from sequences and chromosomes. After a brief survey of molecular biology, it studies restriction maps of DNA, rough landmark maps of the underlying sequences, and clones and clone maps. It examines problems associated with reading DNA sequences and comparing sequences to finding common patterns. The author then considers that statistics of pattern counts in sequences, RNA secondary structure, and the inference of evolutionary history of related sequences. Introduction to Computational Biology exposes the reader to the fascinating structure of biological data and explains how to treat related combinatorial and statistical problems. Written to describe mathematical formulation and development, this book helps set the stage for even more, truly interdisciplinary work in biology.
Research in Computational Molecular Biology by Lenore J. Cowen Pdf
This book constitutes the proceedings of the 23rd Annual Conference on Research in Computational Molecular Biology, RECOMB 2019, held in Washington, DC, USA, in April 2019. The 17 extended and 20 short abstracts presented were carefully reviewed and selected from 175 submissions. The short abstracts are included in the back matter of the volume. The papers report on original research in all areas of computational molecular biology and bioinformatics.
Algorithms in Computational Molecular Biology by Mourad Elloumi,Albert Y. Zomaya Pdf
This book represents the most comprehensive and up-to-date collection of information on the topic of computational molecular biology. Bringing the most recent research into the forefront of discussion, Algorithms in Computational Molecular Biology studies the most important and useful algorithms currently being used in the field, and provides related problems. It also succeeds where other titles have failed, in offering a wide range of information from the introductory fundamentals right up to the latest, most advanced levels of study.
An Introduction to Bioinformatics Algorithms by Neil C. Jones,Pavel A. Pevzner Pdf
An introductory text that emphasizes the underlying algorithmic ideas that are driving advances in bioinformatics. This introductory text offers a clear exposition of the algorithmic principles driving advances in bioinformatics. Accessible to students in both biology and computer science, it strikes a unique balance between rigorous mathematics and practical techniques, emphasizing the ideas underlying algorithms rather than offering a collection of apparently unrelated problems. The book introduces biological and algorithmic ideas together, linking issues in computer science to biology and thus capturing the interest of students in both subjects. It demonstrates that relatively few design techniques can be used to solve a large number of practical problems in biology, and presents this material intuitively. An Introduction to Bioinformatics Algorithms is one of the first books on bioinformatics that can be used by students at an undergraduate level. It includes a dual table of contents, organized by algorithmic idea and biological idea; discussions of biologically relevant problems, including a detailed problem formulation and one or more solutions for each; and brief biographical sketches of leading figures in the field. These interesting vignettes offer students a glimpse of the inspirations and motivations for real work in bioinformatics, making the concepts presented in the text more concrete and the techniques more approachable.PowerPoint presentations, practical bioinformatics problems, sample code, diagrams, demonstrations, and other materials can be found at the Author's website.
Computational Molecular Biology by Peter Clote,Rolf Backofen Pdf
Recently molecular biology has undergone unprecedented developmentgenerating vast quantities of data needing sophisticatedcomputational methods for analysis, processing and archiving. Thisrequirement has given birth to the truly interdisciplinary field ofcomputational biology, or bioinformatics, a subject reliant on boththeoretical and practical contributions from statistics,mathematics, computer science and biology. * Provides the background mathematics required to understand whycertain algorithms work * Guides the reader through probability theory, entropy andcombinatorial optimization * In-depth coverage of molecular biology and protein structureprediction * Includes several less familiar algorithms such as DNAsegmentation, quartet puzzling and DNA strand separationprediction * Includes class tested exercises useful for self-study * Source code of programs available on a Web site Primarily aimed at advanced undergraduate and graduate studentsfrom bioinformatics, computer science, statistics, mathematics andthe biological sciences, this text will also interest researchersfrom these fields.
Computational Methods in Molecular Biology by S.L. Salzberg,D.B. Searls,S. Kasif Pdf
Computational biology is a rapidly expanding field, and the number and variety of computational methods used for DNA and protein sequence analysis is growing every day. These algorithms are extremely valuable to biotechnology companies and to researchers and teachers in universities. This book explains the latest computer technology for analyzing DNA, RNA, and protein sequences. Clear and easy to follow, designed specifically for the non-computer scientist, it will help biologists make better choices on which algorithm to use. New techniques and demonstrations are elucidated, as are state-of-the-art problems, and more advanced material on the latest algorithms. The primary audience for this volume are molecular biologists working either in biotechnology companies or academic research environments, individual researchers and the institutions they work for, and students. Any biologist who relies on computers should want this book. A secondary audience will be computer scientists developing techniques with applications in biology. An excellent reference for leading techniques, it will also help introduce computer scientists to the biology problems. This is an outstanding work which will be ideal for the increasing number of scientists moving into computational biology.
