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Computational Genome Analysis by Richard C. Deonier,Simon Tavaré,Michael S. Waterman Pdf
This book presents the foundations of key problems in computational molecular biology and bioinformatics. It focuses on computational and statistical principles applied to genomes, and introduces the mathematics and statistics that are crucial for understanding these applications. The book features a free download of the R software statistics package and the text provides great crossover material that is interesting and accessible to students in biology, mathematics, statistics and computer science. More than 100 illustrations and diagrams reinforce concepts and present key results from the primary literature. Exercises are given at the end of chapters.
Computational Genomics with R by Altuna Akalin Pdf
Computational Genomics with R provides a starting point for beginners in genomic data analysis and also guides more advanced practitioners to sophisticated data analysis techniques in genomics. The book covers topics from R programming, to machine learning and statistics, to the latest genomic data analysis techniques. The text provides accessible information and explanations, always with the genomics context in the background. This also contains practical and well-documented examples in R so readers can analyze their data by simply reusing the code presented. As the field of computational genomics is interdisciplinary, it requires different starting points for people with different backgrounds. For example, a biologist might skip sections on basic genome biology and start with R programming, whereas a computer scientist might want to start with genome biology. After reading: You will have the basics of R and be able to dive right into specialized uses of R for computational genomics such as using Bioconductor packages. You will be familiar with statistics, supervised and unsupervised learning techniques that are important in data modeling, and exploratory analysis of high-dimensional data. You will understand genomic intervals and operations on them that are used for tasks such as aligned read counting and genomic feature annotation. You will know the basics of processing and quality checking high-throughput sequencing data. You will be able to do sequence analysis, such as calculating GC content for parts of a genome or finding transcription factor binding sites. You will know about visualization techniques used in genomics, such as heatmaps, meta-gene plots, and genomic track visualization. You will be familiar with analysis of different high-throughput sequencing data sets, such as RNA-seq, ChIP-seq, and BS-seq. You will know basic techniques for integrating and interpreting multi-omics datasets. Altuna Akalin is a group leader and head of the Bioinformatics and Omics Data Science Platform at the Berlin Institute of Medical Systems Biology, Max Delbrück Center, Berlin. He has been developing computational methods for analyzing and integrating large-scale genomics data sets since 2002. He has published an extensive body of work in this area. The framework for this book grew out of the yearly computational genomics courses he has been organizing and teaching since 2015.
Introduction to Computational Genomics by Nello Cristianini,Matthew W. Hahn Pdf
Where did SARS come from? Have we inherited genes from Neanderthals? How do plants use their internal clock? The genomic revolution in biology enables us to answer such questions. But the revolution would have been impossible without the support of powerful computational and statistical methods that enable us to exploit genomic data. Many universities are introducing courses to train the next generation of bioinformaticians: biologists fluent in mathematics and computer science, and data analysts familiar with biology. This readable and entertaining book, based on successful taught courses, provides a roadmap to navigate entry to this field. It guides the reader through key achievements of bioinformatics, using a hands-on approach. Statistical sequence analysis, sequence alignment, hidden Markov models, gene and motif finding and more, are introduced in a rigorous yet accessible way. A companion website provides the reader with Matlab-related software tools for reproducing the steps demonstrated in the book.
Computational Exome and Genome Analysis by Peter N. Robinson,Rosario Michael Piro,Marten Jager Pdf
Exome and genome sequencing are revolutionizing medical research and diagnostics, but the computational analysis of the data has become an extremely heterogeneous and often challenging area of bioinformatics. Computational Exome and Genome Analysis provides a practical introduction to all of the major areas in the field, enabling readers to develop a comprehensive understanding of the sequencing process and the entire computational analysis pipeline.
Sequence — Evolution — Function by Eugene V. Koonin,Michael Galperin Pdf
Sequence - Evolution - Function is an introduction to the computational approaches that play a critical role in the emerging new branch of biology known as functional genomics. The book provides the reader with an understanding of the principles and approaches of functional genomics and of the potential and limitations of computational and experimental approaches to genome analysis. Sequence - Evolution - Function should help bridge the "digital divide" between biologists and computer scientists, allowing biologists to better grasp the peculiarities of the emerging field of Genome Biology and to learn how to benefit from the enormous amount of sequence data available in the public databases. The book is non-technical with respect to the computer methods for genome analysis and discusses these methods from the user's viewpoint, without addressing mathematical and algorithmic details. Prior practical familiarity with the basic methods for sequence analysis is a major advantage, but a reader without such experience will be able to use the book as an introduction to these methods. This book is perfect for introductory level courses in computational methods for comparative and functional genomics.
Introduction to Computational Genomics by Nello Cristianini,Matthew W. Hahn Pdf
Where did SARS come from? Have we inherited genes from Neanderthals? How do plants use their internal clock? The genomic revolution in biology enables us to answer such questions. But the revolution would have been impossible without the support of powerful computational and statistical methods that enable us to exploit genomic data. Many universities are introducing courses to train the next generation of bioinformaticians: biologists fluent in mathematics and computer science, and data analysts familiar with biology. This readable and entertaining book, based on successful taught courses, provides a roadmap to navigate entry to this field. It guides the reader through key achievements of bioinformatics, using a hands-on approach. Statistical sequence analysis, sequence alignment, hidden Markov models, gene and motif finding and more, are introduced in a rigorous yet accessible way. A companion website provides the reader with Matlab-related software tools for reproducing the steps demonstrated in the book.
Introduction to Computational Biology by Michael S. Waterman Pdf
Biology is in the midst of a era yielding many significant discoveries and promising many more. Unique to this era is the exponential growth in the size of information-packed databases. Inspired by a pressing need to analyze that data, Introduction to Computational Biology explores a new area of expertise that emerged from this fertile field- the combination of biological and information sciences. This introduction describes the mathematical structure of biological data, especially from sequences and chromosomes. After a brief survey of molecular biology, it studies restriction maps of DNA, rough landmark maps of the underlying sequences, and clones and clone maps. It examines problems associated with reading DNA sequences and comparing sequences to finding common patterns. The author then considers that statistics of pattern counts in sequences, RNA secondary structure, and the inference of evolutionary history of related sequences. Introduction to Computational Biology exposes the reader to the fascinating structure of biological data and explains how to treat related combinatorial and statistical problems. Written to describe mathematical formulation and development, this book helps set the stage for even more, truly interdisciplinary work in biology.
Introduction to Computational Genomics by Nello Cristianini Pdf
Are we related to Neanderthals? Where did SARS come from? Which part of our genome is evolving the fastest? These are some of the questions that can be answered by statistical and computational analysis of genetic data. This text presents an introduction to computational genomics.
Introduction to Computational Biology by Bernhard Haubold,Thomas Wiehe Pdf
Written with the advanced undergraduate in mind, this book introduces into the field of Bioinformatics. The authors explain the computational and conceptional background to the analysis of large-scale sequence data. Many of the corresponding analysis methods are rooted in evolutionary thinking, which serves as a common thread throughout the book. The focus is on methods of comparative genomics and subjects covered include: alignments, gene finding, phylogeny, and the analysis of single nucleotide polymorphisms (SNPs). The volume contains exercises, questions & answers to selected problems.
Applied Computational Genomics by Yin Yao Shugart Pdf
"Applied Computational Genomics" focuses on an in-depth review of statistical development and application in the area of human genomics including candidate gene mapping, linkage analysis, population-based, genome-wide association, exon sequencing and whole genome sequencing analysis. The authors are extremely experienced in the area of statistical genomics and will give a detailed introduction of the evolution in the field and critical evaluations of the advantages and disadvantages of the statistical models proposed. They will also share their views on a future shift toward translational biology. The book will be of value to human geneticists, medical doctors, health educators, policy makers, and graduate students majoring in biology, biostatistics, and bioinformatics. Dr. Yin Yao Shugart is investigator in the Intramural Research Program at the National Institute of Mental Health, Bethesda, Maryland USA.
Introduction To Computational Metagenomics by Zhong Wang Pdf
Breakthroughs in high-throughput genome sequencing and high-performance computing technologies have empowered scientists to decode many genomes including our own. Now they have a bigger ambition: to fully understand the vast diversity of microbial communities within us and around us, and to exploit their potential for the improvement of our health and environment. In this new field called metagenomics, microbial genomes are sequenced directly from the habitats without lab cultivation. Computational metagenomics, however, faces both a data challenge that deals with tens of tera-bases of sequences and an algorithmic one that deals with the complexity of thousands of species and their interactions.This interdisciplinary book is essential reading for those who are interested in beginning their own journey in computational metagenomics. It is a prism to look through various intricate computational metagenomics problems and unravel their three distinctive aspects: metagenomics, data engineering, and algorithms. Graduate students and advanced undergraduates from genomics science or computer science fields will find that the concepts explained in this book can serve as stepping stones for more advanced topics, while metagenomics practitioners and researchers from similar disciplines may use it to broaden their knowledge or identify new research targets.
Introduction to Computational Proteomics by Golan Yona Pdf
Introduction to Computational Proteomics introduces the field of computational biology through a focused approach that tackles the different steps and problems involved with protein analysis, classification, and meta-organization. The book starts with the analysis of individual entities and works its way through the analysis of more complex entitie
Computational Methods for Understanding Bacterial and Archaeal Genomes by Ying Xu,J. Peter Gogarten Pdf
Over 500 prokaryotic genomes have been sequenced to date, and thousands more have been planned for the next few years. While these genomic sequence data provide unprecedented opportunities for biologists to study the world of prokaryotes, they also raise extremely challenging issues such as how to decode the rich information encoded in these genomes. This comprehensive volume includes a collection of cohesively written chapters on prokaryotic genomes, their organization and evolution, the information they encode, and the computational approaches needed to derive such information. A comparative view of bacterial and archaeal genomes, and how information is encoded differently in them, is also presented. Combining theoretical discussions and computational techniques, the book serves as a valuable introductory textbook for graduate-level microbial genomics and informatics courses.
