Discrete and Topological Models in Molecular Biology

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Publisher : Springer Science & Business Media
ISBN 13 : 3642401937
Total Pages : 522 pages
Book Rating : 4.30/5 ( download)

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Book Synopsis Discrete and Topological Models in Molecular Biology by : Nataša Jonoska

Download or read book Discrete and Topological Models in Molecular Biology written by Nataša Jonoska and published by Springer Science & Business Media. This book was released on 2013-12-23 with total page 522 pages. Available in PDF, EPUB and Kindle. Book excerpt: Theoretical tools and insights from discrete mathematics, theoretical computer science, and topology now play essential roles in our understanding of vital biomolecular processes. The related methods are now employed in various fields of mathematical biology as instruments to "zoom in" on processes at a molecular level. This book contains expository chapters on how contemporary models from discrete mathematics – in domains such as algebra, combinatorics, and graph and knot theories – can provide perspective on biomolecular problems ranging from data analysis, molecular and gene arrangements and structures, and knotted DNA embeddings via spatial graph models to the dynamics and kinetics of molecular interactions. The contributing authors are among the leading scientists in this field and the book is a reference for researchers in mathematics and theoretical computer science who are engaged with modeling molecular and biological phenomena using discrete methods. It may also serve as a guide and supplement for graduate courses in mathematical biology or bioinformatics, introducing nontraditional aspects of mathematical biology.

Algebraic and Discrete Mathematical Methods for Modern Biology

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Publisher : Academic Press
ISBN 13 : 0128012714
Total Pages : 382 pages
Book Rating : 4.10/5 ( download)

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Book Synopsis Algebraic and Discrete Mathematical Methods for Modern Biology by : Raina Robeva

Download or read book Algebraic and Discrete Mathematical Methods for Modern Biology written by Raina Robeva and published by Academic Press. This book was released on 2015-05-09 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 description of certain mathematical methods and theory appropriate in the search of answers. Every topic provides a fast-track pathway through the problem by presenting the biological foundation, covering the relevant mathematical theory, and highlighting connections between them. Many of the projects and exercises embedded in each chapter utilize specialized software, providing students with much-needed familiarity and experience with computing applications, critical components of the "modern biology" skill set. This book is appropriate for mathematics courses such as finite mathematics, discrete structures, linear algebra, abstract/modern algebra, graph theory, probability, bioinformatics, statistics, biostatistics, and modeling, as well as for biology courses such as genetics, cell and molecular biology, biochemistry, ecology, and evolution. Examines significant questions in modern biology and their mathematical treatments Presents important mathematical concepts and tools in the context of essential biology Features material of interest to students in both mathematics and biology Presents chapters in modular format so coverage need not follow the Table of Contents Introduces projects appropriate for undergraduate research Utilizes freely accessible software for visualization, simulation, and analysis in modern biology Requires no calculus as a prerequisite Provides a complete Solutions Manual Features a companion website with supplementary resources

Topology in Molecular Biology

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Publisher : Springer
ISBN 13 : 9783540234074
Total Pages : 238 pages
Book Rating : 4.71/5 ( download)

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Book Synopsis Topology in Molecular Biology by : Michael I. Monastyrsky

Download or read book Topology in Molecular Biology written by Michael I. Monastyrsky and published by Springer. This book was released on 2006-10-23 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Models and Modeling in the Sciences

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Publisher : Routledge
ISBN 13 : 1317298063
Total Pages : 115 pages
Book Rating : 4.69/5 ( download)

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Book Synopsis Models and Modeling in the Sciences by : Stephen M. Downes

Download or read book Models and Modeling in the Sciences written by Stephen M. Downes and published by Routledge. This book was released on 2020-07-09 with total page 115 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biologists, climate scientists, and economists all rely on models to move their work forward. In this book, Stephen M. Downes explores the use of models in these and other fields to introduce readers to the various philosophical issues that arise in scientific modeling. Readers learn that paying attention to models plays a crucial role in appraising scientific work. This book first presents a wide range of models from a number of different scientific disciplines. After assembling some illustrative examples, Downes demonstrates how models shed light on many perennial issues in philosophy of science and in philosophy in general. Reviewing the range of views on how models represent their targets introduces readers to the key issues in debates on representation, not only in science but in the arts as well. Also, standard epistemological questions are cast in new and interesting ways when readers confront the question, "What makes for a good (or bad) model?" All examples from the sciences and positions in the philosophy of science are presented in an accessible manner. The book is suitable for undergraduates with minimal experience in philosophy and an introductory undergraduate experience in science. Key features: The book serves as a highly accessible philosophical introduction to models and modeling in the sciences, presenting all philosophical and scientific issues in a nontechnical manner. Students and other readers learn to practice philosophy of science by starting with clear examples taken directly from the sciences. While not comprehensive, this book introduces the reader to a wide range of views on key issues in the philosophy of science.

ReCombinatorics

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Publisher : MIT Press
ISBN 13 : 0262324482
Total Pages : 601 pages
Book Rating : 4.89/5 ( download)

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Book Synopsis ReCombinatorics by : Dan Gusfield

Download or read book ReCombinatorics written by Dan Gusfield and published by MIT Press. This book was released on 2014-07-11 with total page 601 pages. Available in PDF, EPUB and Kindle. Book excerpt: Combinatorial structure and algorithms for deducing genetic recombination history, represented by ancestral recombination graphs and other networks, and their role in the emerging field of phylogenetic networks. In this book, Dan Gusfield examines combinatorial algorithms to construct genealogical and exact phylogenetic networks, particularly ancestral recombination graphs (ARGs). The algorithms produce networks (or information about networks) that serve as hypotheses about the true genealogical history of observed biological sequences and can be applied to practical biological problems. Phylogenetic trees have been the traditional means to represent evolutionary history, but there is a growing realization that networks rather than trees are often needed, most notably for recent human history. This has led to the development of ARGs in population genetics and, more broadly, to phylogenetic networks. ReCombinatorics offers an in-depth, rigorous examination of current research on the combinatorial, graph-theoretic structure of ARGs and explicit phylogenetic networks, and algorithms to reconstruct or deduce information about those networks. ReCombinatorics, a groundbreaking contribution to the emerging field of phylogenetic networks, connects and unifies topics in population genetics and phylogenetics that have traditionally been discussed separately and considered to be unrelated. It covers the necessary combinatorial and algorithmic background material; the various biological phenomena; the mathematical, population genetic, and phylogenetic models that capture the essential elements of these phenomena; the combinatorial and algorithmic problems that derive from these models; the theoretical results that have been obtained; related software that has been developed; and some empirical testing of the software on simulated and real biological data.

Emerging Trends in Applications and Infrastructures for Computational Biology, Bioinformatics, and Systems Biology

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Publisher : Morgan Kaufmann
ISBN 13 : 0128042591
Total Pages : 592 pages
Book Rating : 4.95/5 ( download)

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Book Synopsis Emerging Trends in Applications and Infrastructures for Computational Biology, Bioinformatics, and Systems Biology by : Hamid R Arabnia

Download or read book Emerging Trends in Applications and Infrastructures for Computational Biology, Bioinformatics, and Systems Biology written by Hamid R Arabnia and published by Morgan Kaufmann. This book was released on 2016-03-25 with total page 592 pages. Available in PDF, EPUB and Kindle. Book excerpt: Emerging Trends in Applications and Infrastructures for Computational Biology, Bioinformatics, and Systems Biology: Systems and Applications covers the latest trends in the field with special emphasis on their applications. The first part covers the major areas of computational biology, development and application of data-analytical and theoretical methods, mathematical modeling, and computational simulation techniques for the study of biological and behavioral systems. The second part covers bioinformatics, an interdisciplinary field concerned with methods for storing, retrieving, organizing, and analyzing biological data. The book also explores the software tools used to generate useful biological knowledge. The third part, on systems biology, explores how to obtain, integrate, and analyze complex datasets from multiple experimental sources using interdisciplinary tools and techniques, with the final section focusing on big data and the collection of datasets so large and complex that it becomes difficult to process using conventional database management systems or traditional data processing applications. Explores all the latest advances in this fast-developing field from an applied perspective Provides the only coherent and comprehensive treatment of the subject available Covers the algorithm development, software design, and database applications that have been developed to foster research

Machine Learning and Knowledge Discovery in Databases

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Publisher : Springer
ISBN 13 : 3030109283
Total Pages : 866 pages
Book Rating : 4.88/5 ( download)

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Book Synopsis Machine Learning and Knowledge Discovery in Databases by : Michele Berlingerio

Download or read book Machine Learning and Knowledge Discovery in Databases written by Michele Berlingerio and published by Springer. This book was released on 2019-01-22 with total page 866 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three volume proceedings LNAI 11051 – 11053 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2018, held in Dublin, Ireland, in September 2018. The total of 131 regular papers presented in part I and part II was carefully reviewed and selected from 535 submissions; there are 52 papers in the applied data science, nectar and demo track. The contributions were organized in topical sections named as follows: Part I: adversarial learning; anomaly and outlier detection; applications; classification; clustering and unsupervised learning; deep learningensemble methods; and evaluation. Part II: graphs; kernel methods; learning paradigms; matrix and tensor analysis; online and active learning; pattern and sequence mining; probabilistic models and statistical methods; recommender systems; and transfer learning. Part III: ADS data science applications; ADS e-commerce; ADS engineering and design; ADS financial and security; ADS health; ADS sensing and positioning; nectar track; and demo track.

Algebraic and Combinatorial Computational Biology

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Publisher : Academic Press
ISBN 13 : 0128140690
Total Pages : 434 pages
Book Rating : 4.97/5 ( download)

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Book Synopsis Algebraic and Combinatorial Computational Biology by : Raina Robeva

Download or read book Algebraic and Combinatorial Computational Biology written by Raina Robeva and published by Academic Press. This book was released on 2018-10-08 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: Algebraic and Combinatorial Computational Biology introduces students and researchers to a panorama of powerful and current methods for mathematical problem-solving in modern computational biology. Presented in a modular format, each topic introduces the biological foundations of the field, covers specialized mathematical theory, and concludes by highlighting connections with ongoing research, particularly open questions. The work addresses problems from gene regulation, neuroscience, phylogenetics, molecular networks, assembly and folding of biomolecular structures, and the use of clustering methods in biology. A number of these chapters are surveys of new topics that have not been previously compiled into one unified source. These topics were selected because they highlight the use of technique from algebra and combinatorics that are becoming mainstream in the life sciences. Integrates a comprehensive selection of tools from computational biology into educational or research programs Emphasizes practical problem-solving through multiple exercises, projects and spinoff computational simulations Contains scalable material for use in undergraduate and graduate-level classes and research projects Introduces the reader to freely-available professional software Supported by illustrative datasets and adaptable computer code

Mathematical Models in Biology

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Publisher : Cambridge University Press
ISBN 13 : 9780521525862
Total Pages : 388 pages
Book Rating : 4.61/5 ( download)

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Book Synopsis Mathematical Models in Biology by : Elizabeth Spencer Allman

Download or read book Mathematical Models in Biology written by Elizabeth Spencer Allman and published by Cambridge University Press. This book was released on 2004 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: This introductory textbook on mathematical biology focuses on discrete models across a variety of biological subdisciplines. Biological topics treated include linear and non-linear models of populations, Markov models of molecular evolution, phylogenetic tree construction, genetics, and infectious disease models. The coverage of models of molecular evolution and phylogenetic tree construction from DNA sequence data is unique among books at this level. Computer investigations with MATLAB are incorporated throughout, in both exercises and more extensive projects, to give readers hands-on experience with the mathematical models developed. MATLAB programs accompany the text. Mathematical tools, such as matrix algebra, eigenvector analysis, and basic probability, are motivated by biological models and given self-contained developments, so that mathematical prerequisites are minimal.

Integer Linear Programming in Computational and Systems Biology

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Publisher : Cambridge University Press
ISBN 13 : 1108386253
Total Pages : 431 pages
Book Rating : 4.58/5 ( download)

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Book Synopsis Integer Linear Programming in Computational and Systems Biology by : Dan Gusfield

Download or read book Integer Linear Programming in Computational and Systems Biology written by Dan Gusfield and published by Cambridge University Press. This book was released on 2019-06-13 with total page 431 pages. Available in PDF, EPUB and Kindle. Book excerpt: Integer linear programming (ILP) is a versatile modeling and optimization technique that is increasingly used in non-traditional ways in biology, with the potential to transform biological computation. However, few biologists know about it. This how-to and why-do text introduces ILP through the lens of computational and systems biology. It uses in-depth examples from genomics, phylogenetics, RNA, protein folding, network analysis, cancer, ecology, co-evolution, DNA sequencing, sequence analysis, pedigree and sibling inference, haplotyping, and more, to establish the power of ILP. This book aims to teach the logic of modeling and solving problems with ILP, and to teach the practical 'work flow' involved in using ILP in biology. Written for a wide audience, with no biological or computational prerequisites, this book is appropriate for entry-level and advanced courses aimed at biological and computational students, and as a source for specialists. Numerous exercises and accompanying software (in Python and Perl) demonstrate the concepts.