Genome Data Analysis PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Genome Data Analysis PDF full book. Access full book title Genome Data Analysis by Ju Han Kim. Download full books in PDF and EPUB format.
Author: Ju Han Kim
Publisher: Springer
ISBN: 9811319421
Category : Science
Languages : en
Pages : 367
Get Book Here
Book Description
This textbook describes recent advances in genomics and bioinformatics and provides numerous examples of genome data analysis that illustrate its relevance to real world problems and will improve the reader’s bioinformatics skills. Basic data preprocessing with normalization and filtering, primary pattern analysis, and machine learning algorithms using R and Python are demonstrated for gene-expression microarrays, genotyping microarrays, next-generation sequencing data, epigenomic data, and biological network and semantic analyses. In addition, detailed attention is devoted to integrative genomic data analysis, including multivariate data projection, gene-metabolic pathway mapping, automated biomolecular annotation, text mining of factual and literature databases, and integrated management of biomolecular databases. The textbook is primarily intended for life scientists, medical scientists, statisticians, data processing researchers, engineers, and other beginners in bioinformatics who are experiencing difficulty in approaching the field. However, it will also serve as a simple guideline for experts unfamiliar with the new, developing subfield of genomic analysis within bioinformatics.
Author: Ju Han Kim
Publisher: Springer
ISBN: 9811319421
Category : Science
Languages : en
Pages : 367
Get Book Here
Book Description
This textbook describes recent advances in genomics and bioinformatics and provides numerous examples of genome data analysis that illustrate its relevance to real world problems and will improve the reader’s bioinformatics skills. Basic data preprocessing with normalization and filtering, primary pattern analysis, and machine learning algorithms using R and Python are demonstrated for gene-expression microarrays, genotyping microarrays, next-generation sequencing data, epigenomic data, and biological network and semantic analyses. In addition, detailed attention is devoted to integrative genomic data analysis, including multivariate data projection, gene-metabolic pathway mapping, automated biomolecular annotation, text mining of factual and literature databases, and integrated management of biomolecular databases. The textbook is primarily intended for life scientists, medical scientists, statisticians, data processing researchers, engineers, and other beginners in bioinformatics who are experiencing difficulty in approaching the field. However, it will also serve as a simple guideline for experts unfamiliar with the new, developing subfield of genomic analysis within bioinformatics.
Author: Richard C. Deonier
Publisher: Springer Science & Business Media
ISBN: 0387288074
Category : Computers
Languages : en
Pages : 543
Get Book Here
Book Description
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.
Author: National Research Council
Publisher: National Academies Press
ISBN: 0309038405
Category : Science
Languages : en
Pages : 128
Get Book Here
Book Description
There is growing enthusiasm in the scientific community about the prospect of mapping and sequencing the human genome, a monumental project that will have far-reaching consequences for medicine, biology, technology, and other fields. But how will such an effort be organized and funded? How will we develop the new technologies that are needed? What new legal, social, and ethical questions will be raised? Mapping and Sequencing the Human Genome is a blueprint for this proposed project. The authors offer a highly readable explanation of the technical aspects of genetic mapping and sequencing, and they recommend specific interim and long-range research goals, organizational strategies, and funding levels. They also outline some of the legal and social questions that might arise and urge their early consideration by policymakers.
Author: Daniel O. Stram
Publisher: Springer Science & Business Media
ISBN: 1461494435
Category : Medical
Languages : en
Pages : 344
Get Book Here
Book Description
This book presents the statistical aspects of designing, analyzing and interpreting the results of genome-wide association scans (GWAS studies) for genetic causes of disease using unrelated subjects. Particular detail is given to the practical aspects of employing the bioinformatics and data handling methods necessary to prepare data for statistical analysis. The goal in writing this book is to give statisticians, epidemiologists, and students in these fields the tools to design a powerful genome-wide study based on current technology. The other part of this is showing readers how to conduct analysis of the created study. Design and Analysis of Genome-Wide Association Studies provides a compendium of well-established statistical methods based upon single SNP associations. It also provides an introduction to more advanced statistical methods and issues. Knowing that technology, for instance large scale SNP arrays, is quickly changing, this text has significant lessons for future use with sequencing data. Emphasis on statistical concepts that apply to the problem of finding disease associations irrespective of the technology ensures its future applications. The author includes current bioinformatics tools while outlining the tools that will be required for use with extensive databases from future large scale sequencing projects. The author includes current bioinformatics tools while outlining additional issues and needs arising from the extensive databases from future large scale sequencing projects.
Author: Michal Janitz
Publisher: John Wiley & Sons
ISBN: 3527644733
Category : Science
Languages : en
Pages : 281
Get Book Here
Book Description
Written by leading experts from industry and academia, this first single comprehensive resource addresses recent developments in next generation DNA sequencing technology and their impact on genome research, drug discovery and health care. As such, it presents a detailed comparative analysis of commercially available platforms as well as insights into alternative, emerging sequencing techniques. In addition, the book not only covers the principles of DNA sequencing techniques but also social, ethical and commercial aspects, the concept of personalized medicine and a five-year perspective of DNA sequencing.
Author: Peter N. Robinson
Publisher: CRC Press
ISBN: 1498775993
Category : Computers
Languages : en
Pages : 575
Get Book Here
Book Description
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.
Author: Altuna Akalin
Publisher: CRC Press
ISBN: 1498781861
Category : Mathematics
Languages : en
Pages : 463
Get Book Here
Book Description
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.
Author: Sandy B. Primrose
Publisher: John Wiley & Sons
ISBN: 144431128X
Category : Science
Languages : en
Pages : 288
Get Book Here
Book Description
With the first draft of the human genome project in the publicdomain and full analyses of model genomes now available, thesubject matter of 'Principles of Genome Analysis and Genomics' iseven 'hotter' now than when the first two editions were publishedin 1995 and 1998. In the new edition of this very practical guideto the different techniques and theory behind genomes and genomeanalysis, Sandy Primrose and new author Richard Twyman provide afresh look at this topic. In the light of recent excitingadvancements in the field, the authors have completely revised andrewritten many parts of the new edition with the addition of fivenew chapters. Aimed at upper level students, it is essential thatin this extremely fast moving topic area the text is up to date andrelevant. Completely revised new edition of an establishedtextbook. Features new chapters and examples from exciting new researchin genomics, including the human genome project. Excellent new co-author in Richard Twyman, also co-author ofthe new edition of hugely popular Principles of GeneManipulation. Accompanying web-page to help students deal with this difficulttopic at www.blackwellpublishing.com/primrose
Author: Alain Bernot
Publisher: John Wiley and Sons
ISBN: 0470299568
Category : Science
Languages : en
Pages : 249
Get Book Here
Book Description
Genome Transcriptome and Proteome Analysis is a concise introduction to the subject, successfully bringing together these three key areas of research. Starting with a revision of molecular genetics the book offers clear explanations of the tools and techniques widely used in genome, transcriptome and proteome analysis. Subsequent chapters offer a broad overview of linkage maps, physical maps and genome sequencing, with a final discussion on the identification of genes responsible for disease. An invaluable introduction to the basic concepts of the subject, this text offers the student an excellent overview of current research methods and applications and is a good starting point for those new to the area. A clear, concise introduction to the subject of modern genomic analysis A technology-oriented approach including the latest developments in the field Invaluable to those students taking courses in Bioinformatics, Human Genetics, Biochemistry and Molecular Biology
Author: Kevin Davies
Publisher: Simon and Schuster
ISBN: 1416569618
Category : Medical
Languages : en
Pages : 352
Get Book Here
Book Description
In 2000, President Bill Clinton signaled the completion of the Human Genome Project at a cost in excess of $2 billion. A decade later, the price for any of us to order our own personal genome sequence--a comprehensive map of the 3 billion letters in our DNA--is rapidly and inevitably dropping to just $1,000. Dozens of men and women--scientists, entrepreneurs, celebrities, and patients--have already been sequenced, pioneers in a bold new era of personalized genomic medicine. The $1,000 genome has long been considered the tipping point that would open the floodgates to this revolution. Do you have gene variants associated with Alzheimer's or diabetes, heart disease or cancer? Which drugs should you consider taking for various diseases, and at what dosage? In the years to come, doctors will likely be able to tackle all of these questions--and many more--by using a computer in their offices to call up your unique genome sequence, which will become as much a part of your medical record as your blood pressure.
