Applied Computational Genomics

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Applied Computational Genomics

Author : Yin Yao Shugart
Publisher : Springer Science & Business Media
ISBN 13 : 9400755589
Total Pages : 197 pages
Book Rating : 4.4/5 (7 download)

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Book Synopsis Applied Computational Genomics by : Yin Yao Shugart

Download or read book Applied Computational Genomics written by Yin Yao Shugart and published by Springer Science & Business Media. This book was released on 2012-12-30 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: "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.

Applied Computational Genomics

Author : Yin Yao
Publisher : Springer
ISBN 13 : 9811310718
Total Pages : 150 pages
Book Rating : 4.8/5 (113 download)

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Book Synopsis Applied Computational Genomics by : Yin Yao

Download or read book Applied Computational Genomics written by Yin Yao and published by Springer. This book was released on 2018-09-03 with total page 150 pages. Available in PDF, EPUB and Kindle. Book excerpt: The volume provides a 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 field of statistical genomics and will give a detailed introduction to the evolution of the field, as well as critical comments on the advantages and disadvantages of the proposed statistical models. The future directions of translational biology will also be described.

Computational Genomics with R

Author : Altuna Akalin
Publisher : CRC Press
ISBN 13 : 1498781861
Total Pages : 462 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis Computational Genomics with R by : Altuna Akalin

Download or read book Computational Genomics with R written by Altuna Akalin and published by CRC Press. This book was released on 2020-12-16 with total page 462 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Computational Genome Analysis

Author : Richard C. Deonier
Publisher : Springer Science & Business Media
ISBN 13 : 0387288074
Total Pages : 543 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis Computational Genome Analysis by : Richard C. Deonier

Download or read book Computational Genome Analysis written by Richard C. Deonier and published by Springer Science & Business Media. This book was released on 2005-12-27 with total page 543 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Applied Computational Biology and Statistics in Biotechnology and Bioinformatics (Set of 2 Vols).

Author :
Publisher :
ISBN 13 : 9789351244080
Total Pages : 0 pages
Book Rating : 4.2/5 (44 download)

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Book Synopsis Applied Computational Biology and Statistics in Biotechnology and Bioinformatics (Set of 2 Vols). by :

Download or read book Applied Computational Biology and Statistics in Biotechnology and Bioinformatics (Set of 2 Vols). written by and published by . This book was released on 2015 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Applied Computational Biology and Statistics in Biotechnology and Bioinformatics

Author : Ajit Kumar Roy
Publisher : New India Publishing
ISBN 13 : 9789380235929
Total Pages : 646 pages
Book Rating : 4.2/5 (359 download)

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Book Synopsis Applied Computational Biology and Statistics in Biotechnology and Bioinformatics by : Ajit Kumar Roy

Download or read book Applied Computational Biology and Statistics in Biotechnology and Bioinformatics written by Ajit Kumar Roy and published by New India Publishing. This book was released on 2012-01-15 with total page 646 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book entitled "Applied Computational Biology and Statistics in Biotechnology and Bioinformatics" is aimed to cater to the growing demand of academia, researchers and commercial ventures. Altogether there are forty four chapters divided into the following broad sections like 1. Bioinformatics, Genomics and Proteomics, 2. Phylogeny 3. Drug Design and Epigenomics 4. Advanced Computational Tools and Techniques 5. Statistical methods for computational biology, data mining and visualization 6. Socio Economics and Ethics. This book presents the foundations of key problems in computational molecular biology and bioinformatics. It contains basic molecular biology concepts, tools, techniques and ways to measure sequence similarity, presents simple applications of searching sequence databases. After introducing methods for aligning multiple biological sequences and genomes, the text explores applications of the phylogenetic tree, methods for comparing phylogenetic trees, the problem of gene expression and motif finding. Interestingly, it is attempted to introduce computational biology without formulas that presents the biological and computational ideas in a relatively simple manner. It focuses on computational and statistical principles applied to genomes, and introduces the computational statistics that are crucial for understanding and visualization of problems. This makes the material accessible to Statistician and computer scientists without biological training, as well as to biologists with limited background in Statistics and computer science. Furthermore one chapter has been exclusively devoted to computational biology and computational statistics as applied in biotechnology illustrated with methodology, application and interpretation of results. More than four hundred figures, illustrations and diagrams reinforce concepts and present key results from the primary literature that will be very much useful to grasp on the subject, visualize the output and make right interpretation of the result. The book will be useful for all those working in Biotechnology sector in general and particularly researchers working in the laboratories of ICAR, CSIR, SAU's and many more institutions engaged R&D activities.

Computational Genome Analysis

Author : Richard C. Deonier
Publisher : Springer Science & Business Media
ISBN 13 : 0387288074
Total Pages : 542 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis Computational Genome Analysis by : Richard C. Deonier

Download or read book Computational Genome Analysis written by Richard C. Deonier and published by Springer Science & Business Media. This book was released on 2005-12-27 with total page 542 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Introduction to Computational Genomics

Author : Nello Cristianini
Publisher : Cambridge University Press
ISBN 13 : 9780521856034
Total Pages : 200 pages
Book Rating : 4.8/5 (56 download)

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Book Synopsis Introduction to Computational Genomics by : Nello Cristianini

Download or read book Introduction to Computational Genomics written by Nello Cristianini and published by Cambridge University Press. This book was released on 2006-12-14 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 Biology and Bioinformatics

Author : Ka-Chun Wong
Publisher : CRC Press
ISBN 13 : 1498725007
Total Pages : 439 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis Computational Biology and Bioinformatics by : Ka-Chun Wong

Download or read book Computational Biology and Bioinformatics written by Ka-Chun Wong and published by CRC Press. This book was released on 2016-04-27 with total page 439 pages. Available in PDF, EPUB and Kindle. Book excerpt: The advances in biotechnology such as the next generation sequencing technologies are occurring at breathtaking speed. Advances and breakthroughs give competitive advantages to those who are prepared. However, the driving force behind the positive competition is not only limited to the technological advancement, but also to the companion data analy

Genomic Signal Processing

Author : Ilya Shmulevich
Publisher : Princeton University Press
ISBN 13 : 1400865263
Total Pages : 314 pages
Book Rating : 4.4/5 (8 download)

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Book Synopsis Genomic Signal Processing by : Ilya Shmulevich

Download or read book Genomic Signal Processing written by Ilya Shmulevich and published by Princeton University Press. This book was released on 2014-09-08 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Introduction to Computational Genomics

Author : Nello Cristianini
Publisher : Cambridge University Press
ISBN 13 : 1139460153
Total Pages : 7 pages
Book Rating : 4.1/5 (394 download)

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Book Synopsis Introduction to Computational Genomics by : Nello Cristianini

Download or read book Introduction to Computational Genomics written by Nello Cristianini and published by Cambridge University Press. This book was released on 2006-12-14 with total page 7 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Ethics, Computing, and Genomics

Author : Herman T. Tavani
Publisher : Jones & Bartlett Learning
ISBN 13 : 9780763736200
Total Pages : 382 pages
Book Rating : 4.7/5 (362 download)

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Book Synopsis Ethics, Computing, and Genomics by : Herman T. Tavani

Download or read book Ethics, Computing, and Genomics written by Herman T. Tavani and published by Jones & Bartlett Learning. This book was released on 2006 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: Comprised of eighteen chapters contributed by experts in the fields of biology, computer science, information technology, law, and philosophy, Ethics, Computing, and Genomics provides instructors with a flexible resource for undergraduate and graduate courses in an exciting new field of applied ethics: computational genomics. The chapters are organized in a way that takes the reader from a discussion of conceptual frameworks and methodological perspectives, including ethical theory, to an in-depth analysis of controversial issues involving privacy and confidentiality, information consent, and intellectual property. The volume concludes with some predictions about the future of computational genomics, including the role that nanotechnology will likely play as biotechnologies and information technologies continue to converge.

Advances in Bioinformatics

Author : Vijai Singh
Publisher : Springer Nature
ISBN 13 : 9819984017
Total Pages : 365 pages
Book Rating : 4.8/5 (199 download)

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Book Synopsis Advances in Bioinformatics by : Vijai Singh

Download or read book Advances in Bioinformatics written by Vijai Singh and published by Springer Nature. This book was released on with total page 365 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Basics of Bioinformatics

Author : Rui Jiang
Publisher : Springer Science & Business Media
ISBN 13 : 3642389511
Total Pages : 412 pages
Book Rating : 4.6/5 (423 download)

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Book Synopsis Basics of Bioinformatics by : Rui Jiang

Download or read book Basics of Bioinformatics written by Rui Jiang and published by Springer Science & Business Media. This book was released on 2013-11-26 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book outlines 11 courses and 15 research topics in bioinformatics, based on curriculums and talks in a graduate summer school on bioinformatics that was held in Tsinghua University. The courses include: Basics for Bioinformatics, Basic Statistics for Bioinformatics, Topics in Computational Genomics, Statistical Methods in Bioinformatics, Algorithms in Computational Biology, Multivariate Statistical Methods in Bioinformatics Research, Association Analysis for Human Diseases: Methods and Examples, Data Mining and Knowledge Discovery Methods with Case Examples, Applied Bioinformatics Tools, Foundations for the Study of Structure and Function of Proteins, Computational Systems Biology Approaches for Deciphering Traditional Chinese Medicine, and Advanced Topics in Bioinformatics and Computational Biology. This book can serve as not only a primer for beginners in bioinformatics, but also a highly summarized yet systematic reference book for researchers in this field. Rui Jiang and Xuegong Zhang are both professors at the Department of Automation, Tsinghua University, China. Professor Michael Q. Zhang works at the Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA.

Advances in Computers

Author : Marvin Zelkowitz
Publisher : Elsevier
ISBN 13 : 0080466346
Total Pages : 335 pages
Book Rating : 4.0/5 (84 download)

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Book Synopsis Advances in Computers by : Marvin Zelkowitz

Download or read book Advances in Computers written by Marvin Zelkowitz and published by Elsevier. This book was released on 2006-12-11 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of bioinformatics and computational biology arose due to the need to apply techniques from computer science, statistics, informatics, and applied mathematics to solve biological problems. Scientists have been trying to study biology at a molecular level using techniques derived from biochemistry, biophysics, and genetics. Progress has greatly accelerated with the discovery of fast and inexpensive automated DNA sequencing techniques. As the genomes of more and more organisms are sequenced and assembled, scientists are discovering many useful facts by tracing the evolution of organisms by measuring changes in their DNA, rather than through physical characteristics alone. This has led to rapid growth in the related fields of phylogenetics, the study of evolutionary relatedness among various groups of organisms, and comparative genomics, the study of the correspondence between genes and other genomic features in different organisms. Comparing the genomes of organisms has allowed researchers to better understand the features and functions of DNA in individual organisms, as well as provide insights into how organisms evolve over time. The first four chapters of Advances in Computers focus on algorithms for comparing the genomes of different organisms. Possible concrete applications include identifying the basis for genetic diseases and tracking the development and spread of different forms of Avian flu. As researchers begin to better understand the function of DNA, attention has begun shifting towards the actual proteins produced by DNA. The final two chapters explore proteomic techniques for analyzing proteins directly to identify their presence and understand their physical structure. Written by active PhD researchers in computational biology and bioinformatics

Genomics in the Cloud

Author : Geraldine A. Van der Auwera
Publisher : O'Reilly Media
ISBN 13 : 1491975164
Total Pages : 496 pages
Book Rating : 4.4/5 (919 download)

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Book Synopsis Genomics in the Cloud by : Geraldine A. Van der Auwera

Download or read book Genomics in the Cloud written by Geraldine A. Van der Auwera and published by O'Reilly Media. This book was released on 2020-04-02 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data in the genomics field is booming. In just a few years, organizations such as the National Institutes of Health (NIH) will host 50+ petabytes—or over 50 million gigabytes—of genomic data, and they’re turning to cloud infrastructure to make that data available to the research community. How do you adapt analysis tools and protocols to access and analyze that volume of data in the cloud? With this practical book, researchers will learn how to work with genomics algorithms using open source tools including the Genome Analysis Toolkit (GATK), Docker, WDL, and Terra. Geraldine Van der Auwera, longtime custodian of the GATK user community, and Brian O’Connor of the UC Santa Cruz Genomics Institute, guide you through the process. You’ll learn by working with real data and genomics algorithms from the field. This book covers: Essential genomics and computing technology background Basic cloud computing operations Getting started with GATK, plus three major GATK Best Practices pipelines Automating analysis with scripted workflows using WDL and Cromwell Scaling up workflow execution in the cloud, including parallelization and cost optimization Interactive analysis in the cloud using Jupyter notebooks Secure collaboration and computational reproducibility using Terra

Emerging Trends in Computational Biology, Bioinformatics, and Systems Biology

Author : Hamid R Arabnia
Publisher : Morgan Kaufmann
ISBN 13 : 0128026464
Total Pages : 670 pages
Book Rating : 4.1/5 (28 download)

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

Download or read book Emerging Trends in Computational Biology, Bioinformatics, and Systems Biology written by Hamid R Arabnia and published by Morgan Kaufmann. This book was released on 2015-08-11 with total page 670 pages. Available in PDF, EPUB and Kindle. Book excerpt: Emerging Trends in Computational Biology, Bioinformatics, and Systems Biology discusses the latest developments in all aspects of computational biology, bioinformatics, and systems biology and the application of data-analytics and algorithms, mathematical modeling, and simu- lation techniques. • Discusses the development and application of data-analytical and theoretical methods, mathematical modeling, and computational simulation techniques to the study of biological and behavioral systems, including applications in cancer research, computational intelligence and drug design, high-performance computing, and biology, as well as cloud and grid computing for the storage and access of big data sets. • Presents a systematic approach for storing, retrieving, organizing, and analyzing biological data using software tools with applications to general principles of DNA/RNA structure, bioinformatics and applications, genomes, protein structure, and modeling and classification, as well as microarray analysis. • Provides a systems biology perspective, including general guidelines and techniques for obtaining, integrating, and analyzing complex data sets from multiple experimental sources using computational tools and software. Topics covered include phenomics, genomics, epigenomics/epigenetics, metabolomics, cell cycle and checkpoint control, and systems biology and vaccination research. • Explains how to effectively harness the power of Big Data tools when data sets are so large and complex that it is difficult to process them using conventional database management systems or traditional data processing applications. Discusses the development and application of data-analytical and theoretical methods, mathematical modeling and computational simulation techniques to the study of biological and behavioral systems. Presents a systematic approach for storing, retrieving, organizing and analyzing biological data using software tools with applications. Provides a systems biology perspective including general guidelines and techniques for obtaining, integrating and analyzing complex data sets from multiple experimental sources using computational tools and software.