Techniques for the Analysis of Complex Genomes

Techniques for the Analysis of Complex Genomes PDF Author: Rakesh Anand
Publisher: Academic Press
ISBN:
Category : Science
Languages : en
Pages : 268

Get Book Here

Book Description
Current approaches to long-range physical mapping of the human genome; Analysis of genomic DNAs by pulsed-field gel electrophoresis; The bacteriophage P1 cloning system; Construction, characterization and screening of YAC libraries; Cloning human telomeres in yeast artificial chromosomes; Structural instability of YAC clones and the use of recombination-deficient yeast host strains; The analysis of YAC clones; High-density gridded YAC filters: their potential as genome mapping tools; Transcribed sequences within YACs: HTF Island cloning and cDNA library screening; Yeast artificial chromosome modifying vectors: applications for the analysis of complex genomes; Reconstruction of megabase-size genomic regions using overlapping yeast artificial chromosomes; Generation of region-specific probes by microdissection and universal enzymatic DNA amplification.

Techniques for the Analysis of Complex Genomes

Techniques for the Analysis of Complex Genomes PDF Author: Rakesh Anand
Publisher: Academic Press
ISBN:
Category : Science
Languages : en
Pages : 268

Get Book Here

Book Description
Current approaches to long-range physical mapping of the human genome; Analysis of genomic DNAs by pulsed-field gel electrophoresis; The bacteriophage P1 cloning system; Construction, characterization and screening of YAC libraries; Cloning human telomeres in yeast artificial chromosomes; Structural instability of YAC clones and the use of recombination-deficient yeast host strains; The analysis of YAC clones; High-density gridded YAC filters: their potential as genome mapping tools; Transcribed sequences within YACs: HTF Island cloning and cDNA library screening; Yeast artificial chromosome modifying vectors: applications for the analysis of complex genomes; Reconstruction of megabase-size genomic regions using overlapping yeast artificial chromosomes; Generation of region-specific probes by microdissection and universal enzymatic DNA amplification.

Principles of Genome Analysis and Genomics

Principles of Genome Analysis and Genomics PDF 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

Mapping and Sequencing the Human Genome

Mapping and Sequencing the Human Genome PDF 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.

Genetic Analysis of Complex Disease

Genetic Analysis of Complex Disease PDF Author: William K. Scott
Publisher: John Wiley & Sons
ISBN: 1118123913
Category : Science
Languages : en
Pages : 340

Get Book Here

Book Description
Genetic Analysis of Complex Diseases An up-to-date and complete treatment of the strategies, designs and analysis methods for studying complex genetic disease in human beings In the newly revised Third Edition of Genetic Analysis of Complex Diseases, a team of distinguished geneticists delivers a comprehensive introduction to the most relevant strategies, designs and methods of analysis for the study of complex genetic disease in humans. The book focuses on concepts and designs, thereby offering readers a broad understanding of common problems and solutions in the field based on successful applications in the design and execution of genetic studies. This edited volume contains contributions from some of the leading voices in the area and presents new chapters on high-throughput genomic sequencing, copy-number variant analysis and epigenetic studies. Providing clear and easily referenced overviews of the considerations involved in genetic analysis of complex human genetic disease, including sampling, design, data collection, linkage and association studies and social, legal and ethical issues. Genetic Analysis of Complex Diseases also provides: A thorough introduction to study design for the identification of genes in complex traits Comprehensive explorations of basic concepts in genetics, disease phenotype definition and the determination of the genetic components of disease Practical discussions of modern bioinformatics tools for analysis of genetic data Reflecting on responsible conduct of research in genetic studies, as well as linkage analysis and data management New expanded chapter on complex genetic interactions This latest edition of Genetic Analysis of Complex Diseases is a must-read resource for molecular biologists, human geneticists, genetic epidemiologists and pharmaceutical researchers. It is also invaluable for graduate students taking courses in statistical genetics or genetic epidemiology.

Complex Genome Analysis with High-throughput Sequencing Data

Complex Genome Analysis with High-throughput Sequencing Data PDF Author: Xin Li
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

Get Book Here

Book Description
The genomes of most eukaryotes are large and complex. The presence of large amounts of non-coding sequences is a general property of the genomes of complex eukaryotes. High-throughput sequencing is increasingly important for the study of complex genomes. In this dissertation, we focus on two computational problems for high-throughput sequence data analysis, including detecting circular RNA and calling structural variations (especially deletions). Circular RNA (or circRNA) is a kind of non-coding RNA, which consists of a circular configuration through a typical 5' to 3' phosphodiester bond by non-canonical splicing. CircRNA was originally thought as the byproduct from the process of mis-splicing and considered to be of low abundance. Recently, however, circRNA is considered as a new class of functional molecule, and the importance of circRNA in gene regulation and their biological functions in some human diseases have started to be recognized. In this research work, we propose two algorithms to detect potential circRNA. In order to improve the performance of running time, we design an algorithm called CircMarker to find circRNA by creating k-mer table rather than conventional reads mapping. Furthermore, we develop an algorithm named CircDBG by taking advantage of the information from both reads and annotated genome to create de Bruijn graph for circRNA detection, which improves the accuracy and sensitivity. Structural variation (SV), which ranges from 50 bp to ~3 Mb in size, is an important type of genetic variations. Deletion is a type of SV in which a part of a chromosome or a sequence of DNA is lost during DNA replication. In this research work, we develop a new method called EigenDel for detecting genomic deletions. EigenDel first takes advantage of discordant read-pairs and clipped reads to get initial deletion candidates. Then, EigenDel clusters similar deletion candidates together and calls true deletions from each cluster by using unsupervised learning method. EigenDel outperforms other major methods in terms of balancing accuracy and sensitivity as well as reducing bias. Our results in this dissertation show that sequencing data can be used to study complex genomes by using effective computational approaches.

Statistical Methods for the Analysis of Genomic Data

Statistical Methods for the Analysis of Genomic Data PDF Author: Hui Jiang
Publisher: MDPI
ISBN: 3039361406
Category : Science
Languages : en
Pages : 136

Get Book Here

Book Description
In recent years, technological breakthroughs have greatly enhanced our ability to understand the complex world of molecular biology. Rapid developments in genomic profiling techniques, such as high-throughput sequencing, have brought new opportunities and challenges to the fields of computational biology and bioinformatics. Furthermore, by combining genomic profiling techniques with other experimental techniques, many powerful approaches (e.g., RNA-Seq, Chips-Seq, single-cell assays, and Hi-C) have been developed in order to help explore complex biological systems. As a result of the increasing availability of genomic datasets, in terms of both volume and variety, the analysis of such data has become a critical challenge as well as a topic of great interest. Therefore, statistical methods that address the problems associated with these newly developed techniques are in high demand. This book includes a number of studies that highlight the state-of-the-art statistical methods for the analysis of genomic data and explore future directions for improvement.

Sequence — Evolution — Function

Sequence — Evolution — Function PDF Author: Eugene V. Koonin
Publisher: Springer Science & Business Media
ISBN: 1475737831
Category : Science
Languages : en
Pages : 482

Get Book Here

Book Description
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.

Computational Genomics with R

Computational Genomics with R PDF Author: Altuna Akalin
Publisher: CRC Press
ISBN: 1498781861
Category : Mathematics
Languages : en
Pages : 462

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.

Two-Dimensional DNA Typing

Two-Dimensional DNA Typing PDF Author: Andre G Uitterlinden
Publisher: CRC Press
ISBN: 0137914504
Category : Science
Languages : en
Pages : 203

Get Book Here

Book Description
New technology for analyzing complex genomes is an important area of modern molecular biosciences. This book focuses on a recently developed genome scanning method, termed two-dimensional 2-D DNA typing, which is based on a combination of two independent electrophoretic separation principles. When separation according to size is coupled to separation according to base-pair composition, complex genomes can be resolved in a number of DNA fragments. These fragments or subsets can be visualized, for example, by hybridization analysis with specific probes. Genome scanning by 2-D DNA typing finds applications in many areas, such as linkage and association studies for identifying genetic traits in humans, animals and plants, studies on genetic instabilities in cancers, classification studies in bacteria and other lower organisms, studies on human mutation rates, and the identification of mutations in large genes.

Statistical Analysis of Next Generation Sequencing Data

Statistical Analysis of Next Generation Sequencing Data PDF Author: Somnath Datta
Publisher: Springer
ISBN: 3319072129
Category : Medical
Languages : en
Pages : 438

Get Book Here

Book Description
Next Generation Sequencing (NGS) is the latest high throughput technology to revolutionize genomic research. NGS generates massive genomic datasets that play a key role in the big data phenomenon that surrounds us today. To extract signals from high-dimensional NGS data and make valid statistical inferences and predictions, novel data analytic and statistical techniques are needed. This book contains 20 chapters written by prominent statisticians working with NGS data. The topics range from basic preprocessing and analysis with NGS data to more complex genomic applications such as copy number variation and isoform expression detection. Research statisticians who want to learn about this growing and exciting area will find this book useful. In addition, many chapters from this book could be included in graduate-level classes in statistical bioinformatics for training future biostatisticians who will be expected to deal with genomic data in basic biomedical research, genomic clinical trials and personalized medicine. About the editors: Somnath Datta is Professor and Vice Chair of Bioinformatics and Biostatistics at the University of Louisville. He is Fellow of the American Statistical Association, Fellow of the Institute of Mathematical Statistics and Elected Member of the International Statistical Institute. He has contributed to numerous research areas in Statistics, Biostatistics and Bioinformatics. Dan Nettleton is Professor and Laurence H. Baker Endowed Chair of Biological Statistics in the Department of Statistics at Iowa State University. He is Fellow of the American Statistical Association and has published research on a variety of topics in statistics, biology and bioinformatics.