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Software And Methods For Analyzing Molecular Genetic Marker Data
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Book Synopsis Software and Methods for Analyzing Molecular Genetic Marker Data by : Kejun Liu
Download or read book Software and Methods for Analyzing Molecular Genetic Marker Data written by Kejun Liu and published by . This book was released on 2003 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt: Keywords: Genetic Data Analysis, Inbreds, Maize, Marker, CoreSet, PowerMarker.
Book Synopsis Software and Methods for Analyzing Molecular Genetic Marker Data by :
Download or read book Software and Methods for Analyzing Molecular Genetic Marker Data written by and published by . This book was released on 2003 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Genetic analysis of molecular markers has allowed biologists to ask a wide variety of questions. This dissertation explores some aspects of the statistical and computational issues used in the genetic marker data analysis. Chapter 1 gives an introduction to genetic marker data, as well as a brief description to each chapter. Chapter 2 presents the different genetic analyses performed on a large data set and discusses the use of microsatellites to describe the maize germplasm and to improve maize germplasm maintenance. Considerable attention is focused on how the maize germplasm is organized and genetic variation is distributed. A novel maximum likelihood method is developed to estimate the historical contributions for maize inbred lines. Chapter 3 covers a new method for optimal selection of a core set of lines from a large germplasm collection. The simulated annealing algorithm for choosing an optimal k-subset is described and evaluated using the maize germplasm as an example; general constraints are incorporated in the algorithm, and the efficiency of the algorithms is compared to existing methods. Chapter 4 covers a two-stage strategy to partition a chromosomal region into blocks with extensive within-block linkage disequilibrium, and to select the optimal subset of SNPs that essentially captures the haplotype variation within a block. Population simulations suggest that the recursive bisection algorithm for block partitioning is generally reliable for recombination hotspots identification. Maximal entropy theory is applied to choose optimal subset of SNPs. The procedures are evaluated analytically as well as by simulation. The final chapter covers a new software package for genetic marker data analysis. The methods implemented in the package are listed. A brief tutorial is included to illustrate the features of the package. Chapter 5 also describes a new method for estimating population specific F-statistics and an extended algorithm for estimating haplotype fre.
Book Synopsis Handbook on Analyzing Human Genetic Data by : Shili Lin
Download or read book Handbook on Analyzing Human Genetic Data written by Shili Lin and published by Springer Science & Business Media. This book was released on 2009-10-13 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handbook offers guidance on selections of appropriate computational methods and software packages for specific genetic problems. Coverage strikes a balance between methodological expositions and practical guidelines for software selections. Wherever possible, comparisons among competing methods and software are made to highlight the relative advantages and disadvantage of the approaches.
Book Synopsis Statistical Human Genetics by : Robert C. Elston
Download or read book Statistical Human Genetics written by Robert C. Elston and published by Humana Press. This book was released on 2017-10-04 with total page 689 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of this volume is to make computer programs for analyzing human genetic data more easily accessible to the beginner.Statistical Human Genetics: Methods and Protocols, Second Edition provides updated and new chapters detailing genetic terms, analysis software, and how to interpret the program outputs. Written in the highly successful Methods in Molecular Biology series format, the chapters include introductions to their respective topics, step-by-step instructions, and tips on troubleshooting and avoiding known pitfalls. The purpose of Statistical Human Genetics: Methods and Protocols, Second Edition is to ensure successful and meaningful results in the fast-growing field of genetic epidemiology.
Book Synopsis Evaluating Human Genetic Diversity by : National Research Council
Download or read book Evaluating Human Genetic Diversity written by National Research Council and published by National Academies Press. This book was released on 1998-01-19 with total page 101 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book assesses the scientific value and merit of research on human genetic differencesâ€"including a collection of DNA samples that represents the whole of human genetic diversityâ€"and the ethical, organizational, and policy issues surrounding such research. Evaluating Human Genetic Diversity discusses the potential uses of such collection, such as providing insight into human evolution and origins and serving as a springboard for important medical research. It also addresses issues of confidentiality and individual privacy for participants in genetic diversity research studies.
Download or read book Bioinformatics written by David Edwards and published by Springer Science & Business Media. This book was released on 2009-09-03 with total page 450 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bioinformatics is a relatively new field of research. It evolved from the requirement to process, characterize, and apply the information being produced by DNA sequencing technology. The production of DNA sequence data continues to grow exponentially. At the same time, improved bioinformatics such as faster DNA sequence search methods have been combined with increasingly powerful computer systems to process this information. Methods are being developed for the ever more detailed quantification of gene expression, providing an insight into the function of the newly discovered genes, while molecular genetic tools provide a link between these genes and heritable traits. Genetic tests are now available to determine the likelihood of suffering specific ailments and can predict how plant cultivars may respond to the environment. The steps in the translation of the genetic blueprint to the observed phenotype is being increasingly understood through proteome, metabolome and phenome analysis, all underpinned by advances in bioinformatics. Bioinformatics is becoming increasingly central to the study of biology, and a day at a computer can often save a year or more in the laboratory. The volume is intended for graduate-level biology students as well as researchers who wish to gain a better understanding of applied bioinformatics and who wish to use bioinformatics technologies to assist in their research. The volume would also be of value to bioinformatics developers, particularly those from a computing background, who would like to understand the application of computational tools for biological research. Each chapter would include a comprehensive introduction giving an overview of the fundamentals, aimed at introducing graduate students and researchers from diverse backgrounds to the field and bring them up-to-date on the current state of knowledge. To accommodate the broad range of topics in applied bioinformatics, chapters have been grouped into themes: gene and genome analysis, molecular genetic analysis, gene expression analysis, protein and proteome analysis, metabolome analysis, phenome data analysis, literature mining and bioinformatics tool development. Each chapter and theme provides an introduction to the biology behind the data describes the requirements for data processing and details some of the methods applied to the data to enhance biological understanding.
Book Synopsis Weighted Network Analysis by : Steve Horvath
Download or read book Weighted Network Analysis written by Steve Horvath and published by Springer. This book was released on 2014-10-01 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: High-throughput measurements of gene expression and genetic marker data facilitate systems biologic and systems genetic data analysis strategies. Gene co-expression networks have been used to study a variety of biological systems, bridging the gap from individual genes to biologically or clinically important emergent phenotypes.
Book Synopsis Bioinformatics for Geneticists by : Michael R. Barnes
Download or read book Bioinformatics for Geneticists written by Michael R. Barnes and published by John Wiley & Sons. This book was released on 2007-03-13 with total page 576 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise from the reviews: "Without reservation, I endorse this text as the best resource I've encountered that neatly introduces and summarizes many points I've learned through years of experience. The gems of truth found in this book will serve well those who wish to apply bioinformatics in their daily work, as well as help them advise others in this capacity." CIRCGENETICS "This book may really help to get geneticists and bioinformaticians on 'speaking-terms'... contains some essential reading for almost any person working in the field of molecular genetics." EUROPEAN JOURNAL OF HUMAN GENETICS "... an excellent resource... this book should ensure that any researcher's skill base is maintained." GENETICAL RESEARCH “... one of the best available and most accessible texts on bioinformatics and genetics in the postgenome age... The writing is clear, with succinct subsections within each chapter....Without reservation, I endorse this text as the best resource I’ve encountered that neatly introduces and summarizes many points I’ve learned through years of experience. The gems of truth found in this book will serve well those who wish to apply bioinformatics in their daily work, as well as help them advise others in this capacity.” CIRCULATION: CARDIOVASCULAR GENETICS A fully revised version of the successful First Edition, this one-stop reference book enables all geneticists to improve the efficiency of their research. The study of human genetics is moving into a challenging new era. New technologies and data resources such as the HapMap are enabling genome-wide studies, which could potentially identify most common genetic determinants of human health, disease and drug response. With these tremendous new data resources at hand, more than ever care is required in their use. Faced with the sheer volume of genetics and genomic data, bioinformatics is essential to avoid drowning true signal in noise. Considering these challenges, Bioinformatics for Geneticists, Second Edition works at multiple levels: firstly, for the occasional user who simply wants to extract or analyse specific data; secondly, at the level of the advanced user providing explanations of how and why a tool works and how it can be used to greatest effect. Finally experts from fields allied to genetics give insight into the best genomics tools and data to enhance a genetic experiment. Hallmark Features of the Second Edition: Illustrates the value of bioinformatics as a constantly evolving avenue into novel approaches to study genetics The only book specifically addressing the bioinformatics needs of geneticists More than 50% of chapters are completely new contributions Dramatically revised content in core areas of gene and genomic characterisation, pathway analysis, SNP functional analysis and statistical genetics Focused on freely available tools and web-based approaches to bioinformatics analysis, suitable for novices and experienced researchers alike Bioinformatics for Geneticists, Second Edition describes the key bioinformatics and genetic analysis processes that are needed to identify human genetic determinants. The book is based upon the combined practical experience of domain experts from academic and industrial research environments and is of interest to a broad audience, including students, researchers and clinicians working in the human genetics domain.
Book Synopsis Molecular Markers in Plants by : Robert J. Henry
Download or read book Molecular Markers in Plants written by Robert J. Henry and published by John Wiley & Sons. This book was released on 2012-09-27 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: Molecular Markers in Plants surveys an array of technologies used in the molecular analysis of plants. The role molecular markers play in plant improvement has grown significantly as DNA sequencing and high-throughput technologies have matured. This timely review of technologies and techniques will provide readers with a useful resource on the latest molecular technologies. Molecular Markers in Plants not only reviews past achievements, but also catalogs recent advances and looks forward towards the future application of molecular technologies in plant improvement. Opening chapters look at the development of molecular technologies. Subsequent chapters look at a wide range of applications for the use of these advances in fields as diverse as plant breeding, production, biosecurity, and conservation. The final chapters look forward toward future developments in the field. Looking broadly at the field of molecular technologies, Molecular Markers in Plants will be an essential addition to the library of every researcher, institution, and company working in the field of plant improvement.
Book Synopsis Quantitative Trait Loci by : Nicola J. Camp
Download or read book Quantitative Trait Loci written by Nicola J. Camp and published by Boom Koninklijke Uitgevers. This book was released on 2002-04-26 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: In Quantitative Trait Loci: Methods and Protocols, a panel of highly experienced statistical geneticists demonstrate in a step-by-step fashion how to successfully analyze quantitative trait data using a variety of methods and software for the detection and fine mapping of quantitative trait loci (QTL). Writing for the nonmathematician, these experts guide the investigator from the design stage of a project onwards, providing detailed explanations of how best to proceed with each specific analysis, to find and use appropriate software, and to interpret results. Worked examples, citations to key papers, and variations in method ease the way to understanding and successful studies. Among the cutting-edge techniques presented are QTDT methods, variance components methods, and the Markov Chain Monte Carlo method for joint linkage and segregation analysis.
Book Synopsis Statistical and Computational Methods for Molecular Signature Analysis with Applications by : Aravind Subramanian
Download or read book Statistical and Computational Methods for Molecular Signature Analysis with Applications written by Aravind Subramanian and published by . This book was released on 2005 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: With the advent of DNA microarrays, it is now possible to study the expression pattern of an entire genome in a single experiment. Genome-wide expression analysis has become a mainstay of modern genomics over the past decade, as reflected in the publication of more than 1000 papers per year. The challenge is no longer obtaining gene expression profiles, but rather interpreting the resulting data to gain insight into biological mechanisms. A common approach is simply to focus on a handful of genes at the top and bottom of a differentially expressed gene list and attempt to discern telltale clues from these highest-scoring genes. However, there are serious issues with this approach. One may find that no individual genes meet the threshold of statistical significance, because the relevant biological differences are small compared to the inherent noise in mRNA measurement with current microarrays. Alternatively, one may be left with a long list of statistically significant genes without any unifying theme. To address this problem we introduced a statistical methodology called Gene Set Enrichment Analysis (GSEA) for determining whether a given gene set is significantly enriched in a list of gene markers ranked by their correlation with a phenotype of interest. The method uses a random walk statistic to evaluate enrichment and permutation procedures to assess statistical significance. To apply this method we curated a large database of gene sets based on prior biological knowledge, transcriptional profiles from genetic and chemical perturbations, conserved sequence motifs and computational clustering of previous expression data. We provide a mathematical description of the GSEA algorithm and demonstrate its utility through several biological applications. Gene set based analysis of expression datasets revealed novel findings that were not apparent from traditional single-gene analysis. We demonstrate the broad applicability of GSEA through analysis of datasets from complex disorders such as diabetes, oncologic data from leukemia, p53, lung cancers and present a genomic signature based strategy of using animal models to probe human disease. We have created a software implementation and a catalog of gene sets that can be used for GSEA; both are freely available at http://www.broad.mit.edu.ezproxy.bu.edu/GSEA.
Book Synopsis Bioinformatics for DNA Sequence Analysis by : David Posada
Download or read book Bioinformatics for DNA Sequence Analysis written by David Posada and published by Humana Press. This book was released on 2009-05-07 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: The recent accumulation of information from genomes, including their sequences, has resultednotonlyinnewattemptstoansweroldquestionsandsolvelongstandingissues inbiology,butalsointheformulationofnovelhypothesesthatarisepreciselyfromthis wealth of data. The storage, processing, description, transmission, connection, and analysis of these data has prompted bioinformatics to become one the most relevant applied sciences for this new century, walking hand-in-hand with modern molecular biology and clearly impacting areas like biotechnology and biomedicine. Bioinformatics skills have now become essential for many scientists working with DNA sequences. With this idea in mind, this book aims to provide practical guidance andtroubleshootingadviceforthecomputationalanalysisofDNAsequences,covering a range of issues and methods that unveil the multitude of applications and relevance that Bioinformatics has today. The analysis of protein sequences has been purposely excludedtogainfocus.Individualbookchaptersareorientedtowardthedescriptionof theuseofspecificbioinformaticstools,accompaniedbypracticalexamples,adiscussion on the interpretation of results, and specific comments on strengths and limitations of the methods and tools. In a sense, chapters could be seen as enriched task-oriented manuals that will direct the reader in completing specific bioinformatics analyses. The target audience for this book is biochemists, and molecular and evolutionary biologiststhatwanttolearnhowtoanalyzeDNAsequencesinasimplebutmeaningful fashion. Readers do not need a special background in statistics, mathematics, or computer science, just a basic knowledge of molecular biology and genetics. All the tools described in the book are free and all of them can be downloaded or accessed throughtheweb.Mostchapterscouldbeusedforpracticaladvancedundergraduateor graduate-level courses in bioinformatics and molecular evolution.
Download or read book Bioinformatics written by David Edwards and published by Springer. This book was released on 2010-04-29 with total page 451 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bioinformatics is a relatively new field of research. It evolved from the requirement to process, characterize, and apply the information being produced by DNA sequencing technology. The production of DNA sequence data continues to grow exponentially. At the same time, improved bioinformatics such as faster DNA sequence search methods have been combined with increasingly powerful computer systems to process this information. Methods are being developed for the ever more detailed quantification of gene expression, providing an insight into the function of the newly discovered genes, while molecular genetic tools provide a link between these genes and heritable traits. Genetic tests are now available to determine the likelihood of suffering specific ailments and can predict how plant cultivars may respond to the environment. The steps in the translation of the genetic blueprint to the observed phenotype is being increasingly understood through proteome, metabolome and phenome analysis, all underpinned by advances in bioinformatics. Bioinformatics is becoming increasingly central to the study of biology, and a day at a computer can often save a year or more in the laboratory. The volume is intended for graduate-level biology students as well as researchers who wish to gain a better understanding of applied bioinformatics and who wish to use bioinformatics technologies to assist in their research. The volume would also be of value to bioinformatics developers, particularly those from a computing background, who would like to understand the application of computational tools for biological research. Each chapter would include a comprehensive introduction giving an overview of the fundamentals, aimed at introducing graduate students and researchers from diverse backgrounds to the field and bring them up-to-date on the current state of knowledge. To accommodate the broad range of topics in applied bioinformatics, chapters have been grouped into themes: gene and genome analysis, molecular genetic analysis, gene expression analysis, protein and proteome analysis, metabolome analysis, phenome data analysis, literature mining and bioinformatics tool development. Each chapter and theme provides an introduction to the biology behind the data describes the requirements for data processing and details some of the methods applied to the data to enhance biological understanding.
Book Synopsis Evolutionary Genomics by : Maria Anisimova
Download or read book Evolutionary Genomics written by Maria Anisimova and published by Humana Press. This book was released on 2012-03-08 with total page 556 pages. Available in PDF, EPUB and Kindle. Book excerpt: Together with early theoretical work in population genetics, the debate on sources of genetic makeup initiated by proponents of the neutral theory made a solid contribution to the spectacular growth in statistical methodologies for molecular evolution. Evolutionary Genomics: Statistical and Computational Methods is intended to bring together the more recent developments in the statistical methodology and the challenges that followed as a result of rapidly improving sequencing technologies. Presented by top scientists from a variety of disciplines, the collection includes a wide spectrum of articles encompassing theoretical works and hands-on tutorials, as well as many reviews with key biological insight. Volume 2 begins with phylogenomics and continues with in-depth coverage of natural selection, recombination, and genomic innovation. The remaining chapters treat topics of more recent interest, including population genomics, -omics studies, and computational issues related to the handling of large-scale genomic data. Written in the highly successful Methods in Molecular BiologyTM series format, this work provides the kind of advice on methodology and implementation that is crucial for getting ahead in genomic data analyses. Comprehensive and cutting-edge, Evolutionary Genomics: Statistical and Computational Methods is a treasure chest of state-of the-art methods to study genomic and omics data, certain to inspire both young and experienced readers to join the interdisciplinary field of evolutionary genomics.
Book Synopsis Data Mining for Genomics and Proteomics by : Darius M. Dziuda
Download or read book Data Mining for Genomics and Proteomics written by Darius M. Dziuda and published by John Wiley & Sons. This book was released on 2010-07-16 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining for Genomics and Proteomics uses pragmatic examples and a complete case study to demonstrate step-by-step how biomedical studies can be used to maximize the chance of extracting new and useful biomedical knowledge from data. It is an excellent resource for students and professionals involved with gene or protein expression data in a variety of settings.
Book Synopsis Molecular Evolution and Phylogenetics by : Masatoshi Nei
Download or read book Molecular Evolution and Phylogenetics written by Masatoshi Nei and published by Oxford University Press. This book was released on 2000-07-27 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: During the last ten years, remarkable progress has occurred in the study of molecular evolution. Among the most important factors that are responsible for this progress are the development of new statistical methods and advances in computational technology. In particular, phylogenetic analysis of DNA or protein sequences has become a powerful tool for studying molecular evolution. Along with this developing technology, the application of the new statistical and computational methods has become more complicated and there is no comprehensive volume that treats these methods in depth. Molecular Evolution and Phylogenetics fills this gap and present various statistical methods that are easily accessible to general biologists as well as biochemists, bioinformatists and graduate students. The text covers measurement of sequence divergence, construction of phylogenetic trees, statistical tests for detection of positive Darwinian selection, inference of ancestral amino acid sequences, construction of linearized trees, and analysis of allele frequency data. Emphasis is given to practical methods of data analysis, and methods can be learned by working through numerical examples using the computer program MEGA2 that is provided.
Book Synopsis Excerpts from MacClade by : Wayne P. Maddison
Download or read book Excerpts from MacClade written by Wayne P. Maddison and published by . This book was released on 1992 with total page 116 pages. Available in PDF, EPUB and Kindle. Book excerpt: MacClade is a computer program for graphic and interactive analysis of phylogeny and character evolution for Apple Macintosh computers. It displays a cladogram and paints the branches to indicate reconstructed character evolution. The user can manipulate cladograms on screen as MacClade gives diagnostic feedback. Systematics and other evolutionary biologists can use its flexible and analytical tools to examine phylogenies or interpret character evolution in a phylogenetic context, yet its ease of use should allow students to grasp phylogenetic principles in an interactive environment. This is chapters 3-6 of the user's manual.
