Related books on 'computational-biology'
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by: Uri Alon publisher: Chapman and Hall/CRC, published: 2006-07-07 ASIN: 1584886420 EAN: 9781584886426 sales rank: 78961 Thorough and accessible, this book presents the design principles of biological systems, and highlights the recurring circuit elements that make up biological networks. It provides a simple mathematical framework which can be used to understand and even design biological circuits. The textavoids specialist terms, focusing instead on several well-studied biological systems that concisely demonstrate key principles. An Introduction to Systems Biology: Design Principles of Biological Circuits builds a solid foundation for the intuitive understanding of general principles. It encourages the reader to ask why a system is designed in a particular way and then proceeds to answer with simplified models. |
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by: Neil C. Jones publisher: The MIT Press, published: 2004-08-06 ASIN: 0262101068 EAN: 9780262101066 sales rank: 154638 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. |
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by: Pavel A. Pevzner publisher: A Bradford Book, published: 2000-08-21 ASIN: 0262161974 EAN: 9780262161978 sales rank: 579433 In one of the first major texts in the emerging field of computational molecular biology, Pavel Pevzner covers a broad range of algorithmic and combinatorial topics and shows how they are connected to molecular biology and to biotechnology. The book has a substantial "computational biology without formulas" component that presents the biological and computational ideas in a relatively simple manner. This makes the material accessible to computer scientists without biological training, as well as to biologists with limited background in computer science. Computational Molecular Biology series Computer science and mathematics are transforming molecular biology from an informational to a computational science. Drawing on computational, statistical, experimental, and technological methods, the new discipline of computational molecular biology is dramatically increasing the discovery of new technologies and tools for molecular biology. The new MIT Press Computational Molecular Biology series provides a unique venue for the rapid publication of monographs, textbooks, edited collections, reference works, and lecture notes of the highest quality. |
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by: Michael S. Waterman publisher: Chapman and Hall/CRC, published: 1995-06-01 ASIN: 0412993910 EAN: 9780412993916 sales rank: 649035 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. |
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by: Dan Gusfield publisher: Cambridge University Press, published: 1997-05-28 ASIN: 0521585198 EAN: 9780521585194 sales rank: 224982 Traditionally an area of study in computer science, string algorithms have, in recent years, become an increasingly important part of biology, particularly genetics. This volume is a comprehensive look at computer algorithms for string processing. In addition to pure computer science, Gusfield adds extensive discussions on biological problems that are cast as string problems and on methods developed to solve them. This text emphasizes the fundamental ideas and techniques central to today's applications. New approaches to this complex material simplify methods that up to now have been for the specialist alone. With over 400 exercises to reinforce the material and develop additional topics, the book is suitable as a text for graduate or advanced undergraduate students in computer science, computational biology, or bio-informatics. |
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by: Volkhard Helms publisher: Wiley-VCH, published: 2008-08-12 ASIN: 3527315551 EAN: 9783527315550 sales rank: 794177 "This volume contains succinct, yet clear, descriptions of each of these topics and is best suited for readers who are delving into these concepts for the first time." -The Quarterly Review of Biology, 2009 This textbook provides an ideal introduction to computational cell biology for students of biology and bioinformatics. In particular the text focuses on a network-based approach to the study of cellular systems. Almost 30 carefully designed study exercises offer excellent support for those preparing for exams in these subjects, and help introduce the more technical aspects of the topic while keeping maths to a minimum. |
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by: Bruce R. Donald publisher: The MIT Press, published: 2011-06-01 ASIN: 0262015595 EAN: 9780262015592 sales rank: 408767 Using the tools of information technology to understand the molecular machinery of the cell offers both challenges and opportunities to computational scientists. Over the past decade, novel algorithms have been developed both for analyzing biological data and for synthetic biology problems such as protein engineering. This book explains the algorithmic foundations and computational approaches underlying areas of structural biology including NMR (nuclear magnetic resonance); X-ray crystallography; and the design and analysis of proteins, peptides, and small molecules. Each chapter offers a concise overview of important concepts, focusing on a key topic in the field. Four chapters offer a short course in algorithmic and computational issues related to NMR structural biology, giving the reader a useful toolkit with which to approach the fascinating yet thorny computational problems in this area. A recurrent theme is understanding the interplay between biophysical experiments and computational algorithms. The text emphasizes the mathematical foundations of structural biology while maintaining a balance between algorithms and a nuanced understanding of experimental data. Three emerging areas, particularly fertile ground for research students, are highlighted: NMR methodology, design of proteins and other molecules, and the modeling of protein flexibility. The next generation of computational structural biologists will need training in geometric algorithms, provably good approximation algorithms, scientific computation, and an array of techniques for handling noise and uncertainty in combinatorial geometry and computational biophysics. This book is an essential guide for young scientists on their way to research success in this exciting field. |
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by: Edda Klipp publisher: Wiley-VCH, published: 2009-08-12 ASIN: 3527318747 EAN: 9783527318742 sales rank: 113521 "... Boxed summaries at the start of each subchapter and examples illustrated throughout the book highlight the key points and provide clarity. Most chapters conclude with a short problem set, summarising the basic concepts and prompting further thought. This clear text is a useful starting point for anyone aspiring to solve a biological question using systems biology approaches." —Phenotype, 2010 Systems biology is a highly topical discipline at the intersection of biochemistry, cell biology, computer science, and systems engineering. This course book in systems biology is tailored to the needs of advanced students of biology, engineering, and computer science. It has a companion website with solutions to questions in the book, additional chapters, and computer implementations of systems biology models. The book is a follow-up of the very successful Systems Biology in Practice and incorporates the feedback and suggestions of many lecturers worldwide. The interdisciplinary team of acclaimed authors have worked closely together to ensure a comprehensive coverage of the topic in a fluent and compelling style. Further material is available on www.wiley-vch.de/home/systemsbiology Systems Biology in Practice - Praise from the reviews: "...this is one book that I bought for myself as soon as it was published." "This resource does an admirable job of bringing the readers to a level where they can pursue more advanced study and research." "… I am confident that biologists everywhere will benefit from having a copy to hand." |
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by: Jeremy Ramsden publisher: Springer, published: 2010-12-09 ASIN: 1849967644 EAN: 9781849967648 sales rank: 191174 The field of bioinformatics continues to develop energetically. This comprehensive second edition covers new findings using the successful formula of the original text. Bioinformatics: An Introduction is structured into three parts devoted to Information, Biology and Applications. Every section of the book has been thoroughly updated, and expanded where relevant, to take account of significant new discoveries and realizations of the importance of certain concepts. Furthermore new chapters on Algorithms, Data Processing and Biotechnology have been added. Emphasis is placed on the underlying fundamentals and acquisitions of a broad and comprehensive grasp of the field as a whole. This second edition is intended to be a complete study companion for the advanced undergraduate or graduate student. It is self-contained, bringing together the multiple disciplines necessary for a profound grasp of the field into a coherent whole, allowing the reader to gain much insight into the state of art of bioinformatics. |
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by: Richard Durbin publisher: Cambridge University Press, published: 1998-05-13 ASIN: 0521629713 EAN: 9780521629713 sales rank: 176297 Probablistic models are becoming increasingly important in analyzing the huge amount of data being produced by large-scale DNA-sequencing efforts such as the Human Genome Project. For example, hidden Markov models are used for analyzing biological sequences, linguistic-grammar-based probabilistic models for identifying RNA secondary structure, and probabilistic evolutionary models for inferring phylogenies of sequences from different organisms. This book gives a unified, up-to-date and self-contained account, with a Bayesian slant, of such methods, and more generally to probabilistic methods of sequence analysis. Written by an interdisciplinary team of authors, it is accessible to molecular biologists, computer scientists, and mathematicians with no formal knowledge of the other fields, and at the same time presents the state of the art in this new and important field. |