Topological Data Analysis for Genomics and Evolution

Topological Data Analysis for Genomics and Evolution PDF Author: Raúl Rabadán
Publisher: Cambridge University Press
ISBN: 1108753396
Category : Science
Languages : en
Pages : 521

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Book Description
Biology has entered the age of Big Data. The technical revolution has transformed the field, and extracting meaningful information from large biological data sets is now a central methodological challenge. Algebraic topology is a well-established branch of pure mathematics that studies qualitative descriptors of the shape of geometric objects. It aims to reduce questions to a comparison of algebraic invariants, such as numbers, which are typically easier to solve. Topological data analysis is a rapidly-developing subfield that leverages the tools of algebraic topology to provide robust multiscale analysis of data sets. This book introduces the central ideas and techniques of topological data analysis and its specific applications to biology, including the evolution of viruses, bacteria and humans, genomics of cancer and single cell characterization of developmental processes. Bridging two disciplines, the book is for researchers and graduate students in genomics and evolutionary biology alongside mathematicians interested in applied topology.

Topological Data Analysis for Genomics and Evolution

Topological Data Analysis for Genomics and Evolution PDF Author: Raúl Rabadán
Publisher: Cambridge University Press
ISBN: 1108753396
Category : Science
Languages : en
Pages : 521

Get Book Here

Book Description
Biology has entered the age of Big Data. The technical revolution has transformed the field, and extracting meaningful information from large biological data sets is now a central methodological challenge. Algebraic topology is a well-established branch of pure mathematics that studies qualitative descriptors of the shape of geometric objects. It aims to reduce questions to a comparison of algebraic invariants, such as numbers, which are typically easier to solve. Topological data analysis is a rapidly-developing subfield that leverages the tools of algebraic topology to provide robust multiscale analysis of data sets. This book introduces the central ideas and techniques of topological data analysis and its specific applications to biology, including the evolution of viruses, bacteria and humans, genomics of cancer and single cell characterization of developmental processes. Bridging two disciplines, the book is for researchers and graduate students in genomics and evolutionary biology alongside mathematicians interested in applied topology.

Gene Genealogies, Variation and Evolution: A primer in coalescent theory

Gene Genealogies, Variation and Evolution: A primer in coalescent theory PDF Author: Jotun Hein
Publisher: Oxford University Press, USA
ISBN: 9780191546150
Category : Population genetics
Languages : en
Pages : 298

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Book Description
Authored by leading experts, this seminal text presents a straightforward and elementary account of coalescent theory, which is a central concept in the study of genetic sequence variation observed in a population. Rich in examples and illustrations it is ideal for a graduate course in statistics, population, molecular and medical genetics, bioscience and medicine, and for students studying the evolution of human population and disease. It is also an invaluable reference for bioscientists and statisticians in the pharmaceutical industry and academia - ;Coalescent theory is a central concept in the study of genetic sequence variation that probabilistically describes the genealogy relating the sampled sequences. In this text, besides fulfilling the glaring need for such a book, the authors present this theory in a straightforward and elementary manner and describe the statistical and computational methods used in modelling and analyzing genetic sequence variation. Rich in examples and illustrations the book covers basic concepts, complications arising from geographical structure and recombination before considering aspects of statistical inference based on these models. The book ends with chapters on Gene Mapping, which combines sequence variation data with phenotypic data (such as disease) to define areas of the genome where genes are responsible for the trait, and Human Evolution, a research area that is experiencing a renaissance due to the enormous amounts of data produced in molecular studies. Authored by leading experts, this seminal text presents a straightforward and elementary account of coalescent theory, which is a central concept in the study of genetic sequence variation observed in a population. It is highly suitable for a graduate course in statistics, population, molecular and medical genetics, bioscience and medicine and students studying the evolution of human population and disease, and will be an invaluable reference for bioscientists and statisticians in the pharmaceutical industry and academia - ;an excellent and timely book that should appeal to a variety of people in genetics and applied mathematics. - Professor Montgomery Slatkin (Berkeley);the authors are outstanding experts in the field, and the book is topical and timely. - Professor David Balding (Imperial College);Hein, Schierup and Wiuf have written the first general book on the coalescent. It is an engaging combination of clear mathematical derivation and real data examples. - Professor Joe Felsenstein (University of Washington)

Statistics and Truth

Statistics and Truth PDF Author: Calyampudi Radhakrishna Rao
Publisher: World Scientific
ISBN: 9810231113
Category : Mathematics
Languages : en
Pages : 213

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Book Description
Written by one of the top most statisticians with experience in diverse fields of applications of statistics, the book deals with the philosophical and methodological aspects of information technology, collection and analysis of data to provide insight into a problem, whether it is scientific research, policy making by government or decision making in our daily lives.The author dispels the doubts that chance is an expression of our ignorance which makes accurate prediction impossible and illustrates how our thinking has changed with quantification of uncertainty by showing that chance is no longer the obstructor but a way of expressing our knowledge. Indeed, chance can create and help in the investigation of truth. It is eloquently demonstrated with numerous examples of applications that statistics is the science, technology and art of extracting information from data and is based on a study of the laws of chance. It is highlighted how statistical ideas played a vital role in scientific and other investigations even before statistics was recognized as a separate discipline and how statistics is now evolving as a versatile, powerful and inevitable tool in diverse fields of human endeavor such as literature, legal matters, industry, archaeology and medicine.Use of statistics to the layman in improving the quality of life through wise decision making is emphasized.

Knowledge-Based Bioinformatics

Knowledge-Based Bioinformatics PDF Author: Gil Alterovitz
Publisher: John Wiley & Sons
ISBN: 1119995833
Category : Medical
Languages : en
Pages : 306

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Book Description
There is an increasing need throughout the biomedical sciences for a greater understanding of knowledge-based systems and their application to genomic and proteomic research. This book discusses knowledge-based and statistical approaches, along with applications in bioinformatics and systems biology. The text emphasizes the integration of different methods for analysing and interpreting biomedical data. This, in turn, can lead to breakthrough biomolecular discoveries, with applications in personalized medicine. Key Features: Explores the fundamentals and applications of knowledge-based and statistical approaches in bioinformatics and systems biology. Helps readers to interpret genomic, proteomic, and metabolomic data in understanding complex biological molecules and their interactions. Provides useful guidance on dealing with large datasets in knowledge bases, a common issue in bioinformatics. Written by leading international experts in this field. Students, researchers, and industry professionals with a background in biomedical sciences, mathematics, statistics, or computer science will benefit from this book. It will also be useful for readers worldwide who want to master the application of bioinformatics to real-world situations and understand biological problems that motivate algorithms.

Topological Data Analysis

Topological Data Analysis PDF Author: Nils A. Baas
Publisher: Springer Nature
ISBN: 3030434087
Category : Mathematics
Languages : en
Pages : 522

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Book Description
This book gathers the proceedings of the 2018 Abel Symposium, which was held in Geiranger, Norway, on June 4-8, 2018. The symposium offered an overview of the emerging field of "Topological Data Analysis". This volume presents papers on various research directions, notably including applications in neuroscience, materials science, cancer biology, and immune response. Providing an essential snapshot of the status quo, it represents a valuable asset for practitioners and those considering entering the field.

Handbook of Statistical Genomics

Handbook of Statistical Genomics PDF Author: David J. Balding
Publisher: John Wiley & Sons
ISBN: 1119429226
Category : Science
Languages : en
Pages : 1219

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Book Description
A timely update of a highly popular handbook on statistical genomics This new, two-volume edition of a classic text provides a thorough introduction to statistical genomics, a vital resource for advanced graduate students, early-career researchers and new entrants to the field. It introduces new and updated information on developments that have occurred since the 3rd edition. Widely regarded as the reference work in the field, it features new chapters focusing on statistical aspects of data generated by new sequencing technologies, including sequence-based functional assays. It expands on previous coverage of the many processes between genotype and phenotype, including gene expression and epigenetics, as well as metabolomics. It also examines population genetics and evolutionary models and inference, with new chapters on the multi-species coalescent, admixture and ancient DNA, as well as genetic association studies including causal analyses and variant interpretation. The Handbook of Statistical Genomics focuses on explaining the main ideas, analysis methods and algorithms, citing key recent and historic literature for further details and references. It also includes a glossary of terms, acronyms and abbreviations, and features extensive cross-referencing between chapters, tying the different areas together. With heavy use of up-to-date examples and references to web-based resources, this continues to be a must-have reference in a vital area of research. Provides much-needed, timely coverage of new developments in this expanding area of study Numerous, brand new chapters, for example covering bacterial genomics, microbiome and metagenomics Detailed coverage of application areas, with chapters on plant breeding, conservation and forensic genetics Extensive coverage of human genetic epidemiology, including ethical aspects Edited by one of the leading experts in the field along with rising stars as his co-editors Chapter authors are world-renowned experts in the field, and newly emerging leaders. The Handbook of Statistical Genomics is an excellent introductory text for advanced graduate students and early-career researchers involved in statistical genetics.

Analysis of Biological Networks

Analysis of Biological Networks PDF Author: Björn H. Junker
Publisher: John Wiley & Sons
ISBN: 1118209915
Category : Computers
Languages : en
Pages : 278

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Book Description
An introduction to biological networks and methods for their analysis Analysis of Biological Networks is the first book of its kind to provide readers with a comprehensive introduction to the structural analysis of biological networks at the interface of biology and computer science. The book begins with a brief overview of biological networks and graph theory/graph algorithms and goes on to explore: global network properties, network centralities, network motifs, network clustering, Petri nets, signal transduction and gene regulation networks, protein interaction networks, metabolic networks, phylogenetic networks, ecological networks, and correlation networks. Analysis of Biological Networks is a self-contained introduction to this important research topic, assumes no expert knowledge in computer science or biology, and is accessible to professionals and students alike. Each chapter concludes with a summary of main points and with exercises for readers to test their understanding of the material presented. Additionally, an FTP site with links to author-provided data for the book is available for deeper study. This book is suitable as a resource for researchers in computer science, biology, bioinformatics, advanced biochemistry, and the life sciences, and also serves as an ideal reference text for graduate-level courses in bioinformatics and biological research.

Handbook of Discrete and Computational Geometry

Handbook of Discrete and Computational Geometry PDF Author: Csaba D. Toth
Publisher: CRC Press
ISBN: 1351645919
Category : Computers
Languages : en
Pages : 2354

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Book Description
The Handbook of Discrete and Computational Geometry is intended as a reference book fully accessible to nonspecialists as well as specialists, covering all major aspects of both fields. The book offers the most important results and methods in discrete and computational geometry to those who use them in their work, both in the academic world—as researchers in mathematics and computer science—and in the professional world—as practitioners in fields as diverse as operations research, molecular biology, and robotics. Discrete geometry has contributed significantly to the growth of discrete mathematics in recent years. This has been fueled partly by the advent of powerful computers and by the recent explosion of activity in the relatively young field of computational geometry. This synthesis between discrete and computational geometry lies at the heart of this Handbook. A growing list of application fields includes combinatorial optimization, computer-aided design, computer graphics, crystallography, data analysis, error-correcting codes, geographic information systems, motion planning, operations research, pattern recognition, robotics, solid modeling, and tomography.

Topology in Real-World Machine Learning and Data Analysis

Topology in Real-World Machine Learning and Data Analysis PDF Author: Kathryn Hess
Publisher: Frontiers Media SA
ISBN: 2832504124
Category : Science
Languages : en
Pages : 229

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Book Description


Genomic Signal Processing

Genomic Signal Processing PDF Author: Ilya Shmulevich
Publisher: Princeton University Press
ISBN: 1400865263
Category : Science
Languages : en
Pages : 314

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Book Description
Genomic signal processing (GSP) can be defined as the analysis, processing, and use of genomic signals to gain biological knowledge, and the translation of that knowledge into systems-based applications that can be used to diagnose and treat genetic diseases. Situated at the crossroads of engineering, biology, mathematics, statistics, and computer science, GSP requires the development of both nonlinear dynamical models that adequately represent genomic regulation, and diagnostic and therapeutic tools based on these models. This book facilitates these developments by providing rigorous mathematical definitions and propositions for the main elements of GSP and by paying attention to the validity of models relative to the data. Ilya Shmulevich and Edward Dougherty cover real-world situations and explain their mathematical modeling in relation to systems biology and systems medicine. Genomic Signal Processing makes a major contribution to computational biology, systems biology, and translational genomics by providing a self-contained explanation of the fundamental mathematical issues facing researchers in four areas: classification, clustering, network modeling, and network intervention.