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Author: Arthur M. Lesk
Publisher:
ISBN: 0198794142
Category : Science
Languages : en
Pages : 433
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Book Description
Lesk provides an accessible and thorough introduction to a subject which is becoming a fundamental part of biological science today. The text generates an understanding of the biological background of bioinformatics.
Author: Arthur M. Lesk
Publisher:
ISBN: 0198794142
Category : Science
Languages : en
Pages : 433
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Book Description
Lesk provides an accessible and thorough introduction to a subject which is becoming a fundamental part of biological science today. The text generates an understanding of the biological background of bioinformatics.
Author: Arthur M. Lesk
Publisher:
ISBN: 9780191975387
Category : Bioinformatics
Languages : en
Pages : 0
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Book Description
A vast amount of biological information about a wide range of species has become available in recent years as technological advances have significantly reduced the time it takes to sequence a genome or determine a novel protein structure. This text describes how bioinformatics can be used as a powerful set of tools for retrieving and analysing this biological data, and how bioinformatics can be applied to a wide range of disciplines such as molecular biology, medicine, biotechnology, forensic science, and anthropology.
Author: Neil C. Jones
Publisher: MIT Press
ISBN: 9780262101066
Category : Computers
Languages : en
Pages : 460
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Book Description
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.
Author: Anna Tramontano
Publisher: CRC Press
ISBN: 1420010883
Category : Science
Languages : en
Pages : 193
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Book Description
Guiding readers from the elucidation and analysis of a genomic sequence to the prediction of a protein structure and the identification of the molecular function, Introduction to Bioinformatics describes the rationale and limitations of the bioinformatics methods and tools that can help solve biological problems. Requiring only a limited mathematical and statistical background, the book shows how to efficiently apply these approaches to biological data and evaluate the resulting information. The author, an expert bioinformatics researcher, first addresses the ways of storing and retrieving the enormous amount of biological data produced every day and the methods of decrypting the information encoded by a genome. She then covers the tools that can detect and exploit the evolutionary and functional relationships among biological elements. Subsequent chapters illustrate how to predict the three-dimensional structure of a protein. The book concludes with a discussion of the future of bioinformatics. Even though the future will undoubtedly offer new tools for tackling problems, most of the fundamental aspects of bioinformatics will not change. This resource provides the essential information to understand bioinformatics methods, ultimately facilitating in the solution of biological problems.
Author: Henrik Christensen
Publisher: Springer Nature
ISBN: 3031452933
Category : Science
Languages : en
Pages : 257
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Book Description
This updated and extended second edition of the textbook introduces the basic concepts of bioinformatics and enhances students' skills in the use of software and tools relevant to microbiology research. It discusses the most relevant methods for analysing data and teaches readers how to draw valid conclusions from the observations obtained. Free software and servers available on the Internet are presented in an updated version of 2023 and more advanced stand-alone software is proposed as a second option. In addition, new tools for microbial genome analysis and new flowcharts that complement the didactic elements have been added. Exercises and training questionnaires are included at the end of each chapter to facilitate learning. The book is aimed at Ph.D. students and advanced undergraduate students in microbiology, biotechnology, and (veterinary) medicine with little or basic knowledge of bioinformatics.
Author: Attwood
Publisher: Pearson Education India
ISBN: 9788177586411
Category : Bioinformatics
Languages : en
Pages : 260
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Book Description
Author: Stephen A. Krawetz
Publisher: Springer Science & Business Media
ISBN: 1592593356
Category : Science
Languages : en
Pages : 720
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Book Description
to Bioinformatics A Theoretical and Practical Approach Edited by Stephen A. Krawetz, PhD Wayne State University School of Medicine, Detroit MI and David D. Womble, PhD Wayne State University School of Medicine, Detroit, MI ~ Springer Science+ ~ Business Media, LLC © 2003 Springer Science+Business Media New York Originally published by Humana Press !ne. in 2003 Softcover reprint of the hardcover 1 st edition 2003 humanapress.com Ali rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, microfilming, recording, or otherwise without written permission from the Publisher. Ali papers, comments, opinions, conclusions, or recommendations are those of the author(s), and do not necessarily reflect the views of the publisher. This publication is printed on acid-free paper. G) ANSI Z39.48-1984 (American Standards Institute) Permanence of Paper for Printed Library Materials. Production Editor: Mark J. Breaugh. Cover design by Patricia F. Cleary and Paul A. Thiessen. Cover illustration by Paul A. Thiessen, chemicalgraphics.com.
Author: Edward Curry
Publisher: CRC Press
ISBN: 1351015303
Category : Mathematics
Languages : en
Pages : 311
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Book Description
In biological research, the amount of data available to researchers has increased so much over recent years, it is becoming increasingly difficult to understand the current state of the art without some experience and understanding of data analytics and bioinformatics. An Introduction to Bioinformatics with R: A Practical Guide for Biologists leads the reader through the basics of computational analysis of data encountered in modern biological research. With no previous experience with statistics or programming required, readers will develop the ability to plan suitable analyses of biological datasets, and to use the R programming environment to perform these analyses. This is achieved through a series of case studies using R to answer research questions using molecular biology datasets. Broadly applicable statistical methods are explained, including linear and rank-based correlation, distance metrics and hierarchical clustering, hypothesis testing using linear regression, proportional hazards regression for survival data, and principal component analysis. These methods are then applied as appropriate throughout the case studies, illustrating how they can be used to answer research questions. Key Features: · Provides a practical course in computational data analysis suitable for students or researchers with no previous exposure to computer programming. · Describes in detail the theoretical basis for statistical analysis techniques used throughout the textbook, from basic principles · Presents walk-throughs of data analysis tasks using R and example datasets. All R commands are presented and explained in order to enable the reader to carry out these tasks themselves. · Uses outputs from a large range of molecular biology platforms including DNA methylation and genotyping microarrays; RNA-seq, genome sequencing, ChIP-seq and bisulphite sequencing; and high-throughput phenotypic screens. · Gives worked-out examples geared towards problems encountered in cancer research, which can also be applied across many areas of molecular biology and medical research. This book has been developed over years of training biological scientists and clinicians to analyse the large datasets available in their cancer research projects. It is appropriate for use as a textbook or as a practical book for biological scientists looking to gain bioinformatics skills.
Author: Sushmita Mitra
Publisher: CRC Press
ISBN: 1420011782
Category : Business & Economics
Languages : en
Pages : 386
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Book Description
Lucidly Integrates Current Activities Focusing on both fundamentals and recent advances, Introduction to Machine Learning and Bioinformatics presents an informative and accessible account of the ways in which these two increasingly intertwined areas relate to each other. Examines Connections between Machine Learning & Bio
Author: Warren J. Ewens
Publisher: Springer Science & Business Media
ISBN: 0387400826
Category : Science
Languages : en
Pages : 616
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Book Description
Advances in computers and biotechnology have had a profound impact on biomedical research, and as a result complex data sets can now be generated to address extremely complex biological questions. Correspondingly, advances in the statistical methods necessary to analyze such data are following closely behind the advances in data generation methods. The statistical methods required by bioinformatics present many new and difficult problems for the research community. This book provides an introduction to some of these new methods. The main biological topics treated include sequence analysis, BLAST, microarray analysis, gene finding, and the analysis of evolutionary processes. The main statistical techniques covered include hypothesis testing and estimation, Poisson processes, Markov models and Hidden Markov models, and multiple testing methods. The second edition features new chapters on microarray analysis and on statistical inference, including a discussion of ANOVA, and discussions of the statistical theory of motifs and methods based on the hypergeometric distribution. Much material has been clarified and reorganized. The book is written so as to appeal to biologists and computer scientists who wish to know more about the statistical methods of the field, as well as to trained statisticians who wish to become involved with bioinformatics. The earlier chapters introduce the concepts of probability and statistics at an elementary level, but with an emphasis on material relevant to later chapters and often not covered in standard introductory texts. Later chapters should be immediately accessible to the trained statistician. Sufficient mathematical background consists of introductory courses in calculus and linear algebra. The basic biological concepts that are used are explained, or can be understood from the context, and standard mathematical concepts are summarized in an Appendix. Problems are provided at the end of each chapter allowing the reader to develop aspects of the theory outlined in the main text. Warren J. Ewens holds the Christopher H. Brown Distinguished Professorship at the University of Pennsylvania. He is the author of two books, Population Genetics and Mathematical Population Genetics. He is a senior editor of Annals of Human Genetics and has served on the editorial boards of Theoretical Population Biology, GENETICS, Proceedings of the Royal Society B and SIAM Journal in Mathematical Biology. He is a fellow of the Royal Society and the Australian Academy of Science. Gregory R. Grant is a senior bioinformatics researcher in the University of Pennsylvania Computational Biology and Informatics Laboratory. He obtained his Ph.D. in number theory from the University of Maryland in 1995 and his Masters in Computer Science from the University of Pennsylvania in 1999. Comments on the first edition: "This book would be an ideal text for a postgraduate course...[and] is equally well suited to individual study.... I would recommend the book highly." (Biometrics) "Ewens and Grant have given us a very welcome introduction to what is behind those pretty [graphical user] interfaces." (Naturwissenschaften) "The authors do an excellent job of presenting the essence of the material without getting bogged down in mathematical details." (Journal American Statistical Association) "The authors have restructured classical material to a great extent and the new organization of the different topics is one of the outstanding services of the book." (Metrika)
