Introduction to Mathematical Methods in Bioinformatics

This book PDF is perfect for those who love Science genre, written by Alexander Isaev and published by Springer which was released on 04 October 2006 with total hardcover pages 294. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related Introduction to Mathematical Methods in Bioinformatics books below.

Introduction to Mathematical Methods in Bioinformatics

Author	: Alexander Isaev
File Size	: 49,8 Mb
Publisher	: Springer
Language	: English
Release Date	: 04 October 2006
ISBN	: 9783540484264
Pages	: 294 pages

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Introduction to Mathematical Methods in Bioinformatics by Alexander Isaev Book PDF Summary

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.

Introduction to Mathematical Methods in Bioinformatics by Alexander Isaev

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Mathematics of Bioinformatics by Matthew He,Sergey Petoukhov

Mathematics of Bioinformatics: Theory, Methods, andApplications provides a comprehensive format forconnecting and integrating information derived from mathematicalmethods and applying it to the understanding of biologicalsequences, structures, and networks. Each chapter is divided into anumber of sections based on the bioinformatics topics and relatedmathematical theory and methods. Each topic of the

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Theory and Mathematical Methods in Bioinformatics by Shiyi Shen

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

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Theory And Mathematical Methods For Bioinformatics 1 e by Shen,Jack A Tuszynski,Shiyi

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

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Statistical Methods in Bioinformatics by Warren J. Ewens,Gregory R. Grant

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

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Written by experts in both mathematics and biology, Algebraic and Discrete Mathematical Methods for Modern Biology offers a bridge between math and biology, providing a framework for simulating, analyzing, predicting, and modulating the behavior of complex biological systems. Each chapter begins with a question from modern biology, followed by the

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Introduction to Bioinformatics by Anna Tramontano

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

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Algorithms in Bioinformatics by Wing-Kin Sung

Thoroughly Describes Biological Applications, Computational Problems, and Various Algorithmic Solutions Developed from the author's own teaching material, Algorithms in Bioinformatics: A Practical Introduction provides an in-depth introduction to the algorithmic techniques applied in bioinformatics. For each topic, the author clearly details the bi

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