Applied Computational Genomics

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Publisher : Springer Science & Business Media
ISBN 13 : 9400755589
Total Pages : 197 pages
Book Rating : 4.81/5 ( 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. ​

Computational Genomics with R

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Publisher : CRC Press
ISBN 13 : 1498781861
Total Pages : 462 pages
Book Rating : 4.62/5 ( 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.

Applied Computational Genomics

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Publisher : Springer
ISBN 13 : 9811310718
Total Pages : 150 pages
Book Rating : 4.13/5 ( 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 Genome Analysis

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Publisher : Springer Science & Business Media
ISBN 13 : 0387288074
Total Pages : 543 pages
Book Rating : 4.79/5 ( 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.

Genomic Signal Processing

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Publisher : Princeton University Press
ISBN 13 : 1400865263
Total Pages : 314 pages
Book Rating : 4.60/5 ( 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.

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

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Publisher :
ISBN 13 : 9789351244080
Total Pages : 0 pages
Book Rating : 4.83/5 ( 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:

Computational Genome Analysis

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Author :
Publisher : Springer Science & Business Media
ISBN 13 : 0387288074
Total Pages : 542 pages
Book Rating : 4.79/5 ( 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.

Ethics, Computing, and Genomics

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Publisher : Jones & Bartlett Learning
ISBN 13 : 9780763736200
Total Pages : 382 pages
Book Rating : 4.01/5 ( 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.

Applied Computational Biology and Statistics in Biotechnology and Bioinformatics

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Publisher : New India Publishing
ISBN 13 : 9789380235929
Total Pages : 646 pages
Book Rating : 4.25/5 ( 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.

Computing for Comparative Microbial Genomics

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Publisher : Springer Science & Business Media
ISBN 13 : 1848002548
Total Pages : 272 pages
Book Rating : 4.48/5 ( download)

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Book Synopsis Computing for Comparative Microbial Genomics by : David Wayne Ussery

Download or read book Computing for Comparative Microbial Genomics written by David Wayne Ussery and published by Springer Science & Business Media. This book was released on 2009-02-26 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: Overview and Goals This book describes how to visualize and compare bacterial genomes. Sequencing technologies are becoming so inexpensive that soon going for a cup of coffee will be more expensive than sequencing a bacterial genome. Thus, there is a very real and pressing need for high-throughput computational methods to compare hundreds and thousands of bacterial genomes. It is a long road from molecular biology to systems biology, and in a sense this text can be thought of as a path bridging these ? elds. The goal of this book is to p- vide a coherent set of tools and a methodological framework for starting with raw DNA sequences and producing fully annotated genome sequences, and then using these to build up and test models about groups of interacting organisms within an environment or ecological niche. Organization and Features The text is divided into four main parts: Introduction, Comparative Genomics, Transcriptomics and Proteomics, and ? nally Microbial Communities. The ? rst ? ve chapters are introductions of various sorts. Each of these chapters represents an introduction to a speci? c scienti? c ? eld, to bring all readers up to the same basic level before proceeding on to the methods of comparing genomes. First, a brief overview of molecular biology and of the concept of sequences as biological inf- mation are given.