Introduction To Mathematical Methods In Bioinformatics


Introduction To Mathematical Methods In Bioinformatics
DOWNLOAD

Download Introduction To Mathematical Methods In Bioinformatics PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Introduction To Mathematical Methods In Bioinformatics 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. If the content not found or just blank you must refresh this page





Introduction To Mathematical Methods In Bioinformatics


Introduction To Mathematical Methods In Bioinformatics
DOWNLOAD

Author : Alexander Isaev
language : en
Publisher: Springer
Release Date : 2006-10-04

Introduction To Mathematical Methods In Bioinformatics written by Alexander Isaev and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-10-04 with Science categories.


This book looks at the mathematical foundations of the models currently in use. All existing books on bioinformatics are software-orientated and they concentrate on computer implementations of mathematical models of biology. This book is unique in the sense that it looks at the mathematical foundations of the models, which are crucial for correct interpretation of the outputs of the models.



Mathematics Of Bioinformatics


Mathematics Of Bioinformatics
DOWNLOAD

Author : Matthew He
language : en
Publisher: John Wiley & Sons
Release Date : 2011-03-16

Mathematics Of Bioinformatics written by Matthew He and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-03-16 with Computers categories.


Mathematics of Bioinformatics: Theory, Methods, and Applications provides a comprehensive format for connecting and integrating information derived from mathematical methods and applying it to the understanding of biological sequences, structures, and networks. Each chapter is divided into a number of sections based on the bioinformatics topics and related mathematical theory and methods. Each topic of the section is comprised of the following three parts: an introduction to the biological problems in bioinformatics; a presentation of relevant topics of mathematical theory and methods to the bioinformatics problems introduced in the first part; an integrative overview that draws the connections and interfaces between bioinformatics problems/issues and mathematical theory/methods/applications.



Theory And Mathematical Methods In Bioinformatics


Theory And Mathematical Methods In Bioinformatics
DOWNLOAD

Author : Shiyi Shen
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-01-26

Theory And Mathematical Methods In Bioinformatics written by Shiyi Shen and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-01-26 with Science categories.


This monograph addresses, in a systematic and pedagogical manner, the mathematical methods and the algorithms required to deal with the molecularly based problems of bioinformatics. Prominent attention is given to pair-wise and multiple sequence alignment algorithms, stochastic models of mutations, modulus structure theory and protein configuration analysis. Strong links to the molecular structures of proteins, DNA and other biomolecules and their analyses are developed.



Theory And Mathematical Methods For Bioinformatics 1 E


Theory And Mathematical Methods For Bioinformatics 1 E
DOWNLOAD

Author : Shen
language : en
Publisher:
Release Date : 2010-12-01

Theory And Mathematical Methods For Bioinformatics 1 E written by Shen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-12-01 with categories.


This monograph addresses, in a systematic and pedagogical manner, the mathematical methods and the algorithms required to deal with the molecularly based problems of bioinformatics. The book will be useful to students, research scientists and practitioners of bioinformatics and related fields, especially those who are interested in the underlying mathematical methods and theory. Among the methods presented in the book, prominent attention is given to pair-wise and multiple sequence alignment algorithms, stochastic models of mutations, modulus structure theory and protein configuration analysis. Strong links to the molecular structures of proteins, DNA and other biomolecules and their analyses are developed. In particular, for proteins an in-depth exposition of secondary structure prediction methods should be a valuable tool in both molecular biology and in applications to rational drug design. The book can also be used as a textbook and for this reason most of the chapters include exercises and problems at the level of a graduate program in bioinformatics.



Statistical Methods In Bioinformatics


Statistical Methods In Bioinformatics
DOWNLOAD

Author : Warren J. Ewens
language : en
Publisher: Springer Science & Business Media
Release Date : 2005-09-30

Statistical Methods In Bioinformatics written by Warren J. Ewens and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-09-30 with Science categories.


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)



Introduction To Theoretical Population Genetics


Introduction To Theoretical Population Genetics
DOWNLOAD

Author : Thomas Nagylaki
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-12

Introduction To Theoretical Population Genetics written by Thomas Nagylaki and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-12 with Science categories.


This book covers those areas of theoretical population genetics that can be investigated rigorously by elementary mathematical methods. I have tried to formulate the various models fairly generally and to state the biological as sumptions quite explicitly. I hope the choice and treatment of topics will en able the reader to understand and evaluate detailed analyses of many specific models and applications in the literature. Models in population genetics are highly idealized, often even over idealized, and their connection with observation is frequently remote. Further more, it is not practicable to measure the parameters and variables in these models with high accuracy. These regrettable circumstances amply justify the use of appropriate, lucid, and rigorous approximations in the analysis of our models, and such approximations are often illuminating even when exact solu tions are available. However, our empirical and theoretical limitations justify neither opaque, incomplete formulations nor unconvincing, inadequate analy ses, for these may produce uninterpretable, misleading, or erroneous results. Intuition is a principal source of ideas for the construction and investigation of models, but it can replace neither clear formulation nor careful analysis. Fisher (1930; 1958, pp. x, 23-24, 38) not only espoused similar ideas, but he recognized also that our concepts of intuition and rigor must evolve in time. The book is neither a review of the literature nor a compendium of results. The material is almost entirely self-contained. The first eight chapters are a thoroughly revised and greatly extended version of my published lecture notes (Nagylaki, 1977a).



Introduction To Mathematical Methods In Bioinformatics


Introduction To Mathematical Methods In Bioinformatics
DOWNLOAD

Author : Alexander Isaev
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-09-19

Introduction To Mathematical Methods In Bioinformatics written by Alexander Isaev and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-09-19 with Science categories.


This book looks at the mathematical foundations of the models currently in use. All existing books on bioinformatics are software-orientated and they concentrate on computer implementations of mathematical models of biology. This book is unique in the sense that it looks at the mathematical foundations of the models, which are crucial for correct interpretation of the outputs of the models.



Mathematical Modeling Of Biological Systems Volume Ii


Mathematical Modeling Of Biological Systems Volume Ii
DOWNLOAD

Author : Andreas Deutsch
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-10-12

Mathematical Modeling Of Biological Systems Volume Ii written by Andreas Deutsch and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-10-12 with Mathematics categories.


Volume II of this two-volume, interdisciplinary work is a unified presentation of a broad range of state-of-the-art topics in the rapidly growing field of mathematical modeling in the biological sciences. Highlighted throughout are mathematical and computational apporaches to examine central problems in the life sciences, ranging from the organization principles of individual cells to the dynamics of large populations. The chapters are thematically organized into the following main areas: epidemiology, evolution and ecology, immunology, neural systems and the brain, and innovative mathematical methods and education. The work will be an excellent reference text for a broad audience of researchers, practitioners, and advanced students in this rapidly growing field at the intersection of applied mathematics, experimental biology and medicine, computational biology, biochemistry, computer science, and physics.



Statistical Methods In Bioinformatics


Statistical Methods In Bioinformatics
DOWNLOAD

Author : Warren J. Ewens
language : en
Publisher: Springer
Release Date : 2008-11-01

Statistical Methods In Bioinformatics written by Warren J. Ewens and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-11-01 with Science categories.


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)



Introduction To Mathematics For Computational Biology


Introduction To Mathematics For Computational Biology
DOWNLOAD

Author : Paola Lecca
language : en
Publisher: Springer Nature
Release Date : 2023-10-14

Introduction To Mathematics For Computational Biology written by Paola Lecca and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-14 with Science categories.


This introductory guide provides a thorough explanation of the mathematics and algorithms used in standard data analysis techniques within systems biology, biochemistry, and biophysics. Each part of the book covers the mathematical background and practical applications of a given technique. Readers will gain an understanding of the mathematical and algorithmic steps needed to use these software tools appropriately and effectively, as well how to assess their specific circumstance and choose the optimal method and technology. Ideal for students planning for a career in research, early-career researchers, and established scientists undertaking interdisciplinary research.