Download or read book Gene Expression Analysis written by Nalini Raghavachari and published by Humana. This book was released on 2018-05-17 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume provides experimental and bioinformatics approaches related to different aspects of gene expression analysis. Divided in three sections chapters detail wet-lab protocols, bioinformatics approaches, single-cell gene expression, highly multiplexed amplicon sequencing, multi-omics techniques, and targeted sequencing. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Gene Expression Analysis: Methods and Protocols aims provide useful information to researchers worldwide.
Download or read book Molecular Biology of The Cell written by Bruce Alberts and published by . This book was released on 2002 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Statistical Analysis of Gene Expression Microarray Data written by Terry Speed and published by CRC Press. This book was released on 2003-03-26 with total page 237 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although less than a decade old, the field of microarray data analysis is now thriving and growing at a remarkable pace. Biologists, geneticists, and computer scientists as well as statisticians all need an accessible, systematic treatment of the techniques used for analyzing the vast amounts of data generated by large-scale gene expression studies
Download or read book Gene Expression Data Analysis written by Pankaj Barah and published by CRC Press. This book was released on 2021-11-08 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: Development of high-throughput technologies in molecular biology during the last two decades has contributed to the production of tremendous amounts of data. Microarray and RNA sequencing are two such widely used high-throughput technologies for simultaneously monitoring the expression patterns of thousands of genes. Data produced from such experiments are voluminous (both in dimensionality and numbers of instances) and evolving in nature. Analysis of huge amounts of data toward the identification of interesting patterns that are relevant for a given biological question requires high-performance computational infrastructure as well as efficient machine learning algorithms. Cross-communication of ideas between biologists and computer scientists remains a big challenge. Gene Expression Data Analysis: A Statistical and Machine Learning Perspective has been written with a multidisciplinary audience in mind. The book discusses gene expression data analysis from molecular biology, machine learning, and statistical perspectives. Readers will be able to acquire both theoretical and practical knowledge of methods for identifying novel patterns of high biological significance. To measure the effectiveness of such algorithms, we discuss statistical and biological performance metrics that can be used in real life or in a simulated environment. This book discusses a large number of benchmark algorithms, tools, systems, and repositories that are commonly used in analyzing gene expression data and validating results. This book will benefit students, researchers, and practitioners in biology, medicine, and computer science by enabling them to acquire in-depth knowledge in statistical and machine-learning-based methods for analyzing gene expression data. Key Features: An introduction to the Central Dogma of molecular biology and information flow in biological systems A systematic overview of the methods for generating gene expression data Background knowledge on statistical modeling and machine learning techniques Detailed methodology of analyzing gene expression data with an example case study Clustering methods for finding co-expression patterns from microarray, bulkRNA, and scRNA data A large number of practical tools, systems, and repositories that are useful for computational biologists to create, analyze, and validate biologically relevant gene expression patterns Suitable for multidisciplinary researchers and practitioners in computer science and the biological sciences
Download or read book Analyzing Microarray Gene Expression Data written by Geoffrey J. McLachlan and published by John Wiley & Sons. This book was released on 2005-02-18 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: A multi-discipline, hands-on guide to microarray analysis of biological processes Analyzing Microarray Gene Expression Data provides a comprehensive review of available methodologies for the analysis of data derived from the latest DNA microarray technologies. Designed for biostatisticians entering the field of microarray analysis as well as biologists seeking to more effectively analyze their own experimental data, the text features a unique interdisciplinary approach and a combined academic and practical perspective that offers readers the most complete and applied coverage of the subject matter to date. Following a basic overview of the biological and technical principles behind microarray experimentation, the text provides a look at some of the most effective tools and procedures for achieving optimum reliability and reproducibility of research results, including: An in-depth account of the detection of genes that are differentially expressed across a number of classes of tissues Extensive coverage of both cluster analysis and discriminant analysis of microarray data and the growing applications of both methodologies A model-based approach to cluster analysis, with emphasis on the use of the EMMIX-GENE procedure for the clustering of tissue samples The latest data cleaning and normalization procedures The uses of microarray expression data for providing important prognostic information on the outcome of disease
Download or read book Cap Analysis Gene Expression CAGE written by Piero Carninci and published by Pan Stanford Publishing. This book was released on 2010 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a guide for users of new technologies, as it includes accurately proven protocols, allowing readers to prepare their samples for experiments. Although examples mainly concern mammalians, the discussion expands to other groups of eukaryotes, where these approaches are complementing genome sequencing.
Download or read book Bioarrays written by Krishnarao Appasani and published by Springer Science & Business Media. This book was released on 2007-10-04 with total page 269 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an integrated collection of timely articles on the use of bioarray techniques in the fields of biotechnology and molecular medicine. It is the first book to comprehensively integrate molecular diagnostics and molecular pathology. This book serves as an indispensable reference for graduate students, post-docs, and professors as well as an explanatory analysis for executives and scientists in biotechnology and pharmaceutical companies.
Download or read book Weighted Network Analysis written by Steve Horvath and published by Springer Science & Business Media. This book was released on 2011-04-30 with total page 433 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.
Download or read book Bayesian Analysis of Gene Expression Data written by Bani K. Mallick and published by John Wiley & Sons. This book was released on 2009-07-20 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of high-throughput genetic experimentation is evolving rapidly, with the advent of new technologies and new venues for data mining. Bayesian methods play a role central to the future of data and knowledge integration in the field of Bioinformatics. This book is devoted exclusively to Bayesian methods of analysis for applications to high-throughput gene expression data, exploring the relevant methods that are changing Bioinformatics. Case studies, illustrating Bayesian analyses of public gene expression data, provide the backdrop for students to develop analytical skills, while the more experienced readers will find the review of advanced methods challenging and attainable. This book: Introduces the fundamentals in Bayesian methods of analysis for applications to high-throughput gene expression data. Provides an extensive review of Bayesian analysis and advanced topics for Bioinformatics, including examples that extensively detail the necessary applications. Accompanied by website featuring datasets, exercises and solutions. Bayesian Analysis of Gene Expression Data offers a unique introduction to both Bayesian analysis and gene expression, aimed at graduate students in Statistics, Biomedical Engineers, Computer Scientists, Biostatisticians, Statistical Geneticists, Computational Biologists, applied Mathematicians and Medical consultants working in genomics. Bioinformatics researchers from many fields will find much value in this book.
Download or read book Gene Expression Analysis written by Nalini Raghavachari and published by Humana. This book was released on 2019-05-31 with total page 387 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume provides experimental and bioinformatics approaches related to different aspects of gene expression analysis. Divided in three sections chapters detail wet-lab protocols, bioinformatics approaches, single-cell gene expression, highly multiplexed amplicon sequencing, multi-omics techniques, and targeted sequencing. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Gene Expression Analysis: Methods and Protocols aims provide useful information to researchers worldwide.
Download or read book Bayesian Inference for Gene Expression and Proteomics written by Kim-Anh Do and published by Cambridge University Press. This book was released on 2006-07-24 with total page 437 pages. Available in PDF, EPUB and Kindle. Book excerpt: Expert overviews of Bayesian methodology, tools and software for multi-platform high-throughput experimentation.
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.
Download or read book The Analysis of Gene Expression Data written by Giovanni Parmigiani and published by Springer Science & Business Media. This book was released on 2006-04-11 with total page 511 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents practical approaches for the analysis of data from gene expression micro-arrays. It describes the conceptual and methodological underpinning for a statistical tool and its implementation in software. The book includes coverage of various packages that are part of the Bioconductor project and several related R tools. The materials presented cover a range of software tools designed for varied audiences.
Download or read book Microarray Gene Expression Data Analysis written by Helen Causton and published by John Wiley & Sons. This book was released on 2009-04-01 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: This guide covers aspects of designing microarray experiments and analysing the data generated, including information on some of the tools that are available from non-commercial sources. Concepts and principles underpinning gene expression analysis are emphasised and wherever possible, the mathematics has been simplified. The guide is intended for use by graduates and researchers in bioinformatics and the life sciences and is also suitable for statisticians who are interested in the approaches currently used to study gene expression. Microarrays are an automated way of carrying out thousands of experiments at once, and allows scientists to obtain huge amounts of information very quickly Short, concise text on this difficult topic area Clear illustrations throughout Written by well-known teachers in the subject Provides insight into how to analyse the data produced from microarrays
Download or read book Stress and Environmental Regulation of Gene Expression and Adaptation in Bacteria written by Frans J. de Bruijn and published by John Wiley & Sons. This book was released on 2016-07-13 with total page 1472 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bacteria in various habitats are subject to continuously changing environmental conditions, such as nutrient deprivation, heat and cold stress, UV radiation, oxidative stress, dessication, acid stress, nitrosative stress, cell envelope stress, heavy metal exposure, osmotic stress, and others. In order to survive, they have to respond to these conditions by adapting their physiology through sometimes drastic changes in gene expression. In addition they may adapt by changing their morphology, forming biofilms, fruiting bodies or spores, filaments, Viable But Not Culturable (VBNC) cells or moving away from stress compounds via chemotaxis. Changes in gene expression constitute the main component of the bacterial response to stress and environmental changes, and involve a myriad of different mechanisms, including (alternative) sigma factors, bi- or tri-component regulatory systems, small non-coding RNA’s, chaperones, CHRIS-Cas systems, DNA repair, toxin-antitoxin systems, the stringent response, efflux pumps, alarmones, and modulation of the cell envelope or membranes, to name a few. Many regulatory elements are conserved in different bacteria; however there are endless variations on the theme and novel elements of gene regulation in bacteria inhabiting particular environments are constantly being discovered. Especially in (pathogenic) bacteria colonizing the human body a plethora of bacterial responses to innate stresses such as pH, reactive nitrogen and oxygen species and antibiotic stress are being described. An attempt is made to not only cover model systems but give a broad overview of the stress-responsive regulatory systems in a variety of bacteria, including medically important bacteria, where elucidation of certain aspects of these systems could lead to treatment strategies of the pathogens. Many of the regulatory systems being uncovered are specific, but there is also considerable “cross-talk” between different circuits. Stress and Environmental Regulation of Gene Expression and Adaptation in Bacteria is a comprehensive two-volume work bringing together both review and original research articles on key topics in stress and environmental control of gene expression in bacteria. Volume One contains key overview chapters, as well as content on one/two/three component regulatory systems and stress responses, sigma factors and stress responses, small non-coding RNAs and stress responses, toxin-antitoxin systems and stress responses, stringent response to stress, responses to UV irradiation, SOS and double stranded systems repair systems and stress, adaptation to both oxidative and osmotic stress, and desiccation tolerance and drought stress. Volume Two covers heat shock responses, chaperonins and stress, cold shock responses, adaptation to acid stress, nitrosative stress, and envelope stress, as well as iron homeostasis, metal resistance, quorum sensing, chemotaxis and biofilm formation, and viable but not culturable (VBNC) cells. Covering the full breadth of current stress and environmental control of gene expression studies and expanding it towards future advances in the field, these two volumes are a one-stop reference for (non) medical molecular geneticists interested in gene regulation under stress.
Download or read book Serial Analysis of Gene Expression SAGE written by Kåre Lehmann Nielsen and published by Springer Science & Business Media. This book was released on 2008 with total page 213 pages. Available in PDF, EPUB and Kindle. Book excerpt: Serial Analysis of Gene Expression (SAGE): Digital Gene Expression Profiling facilitates the introduction of SAGE into the laboratory, and provides a framework for interpreting and comparing data derived from SAGE experiments. Of the several methods of genetic profiling available, only SAGE measures the expression of both known and unknown genes. SAGE studies encompass 50,000 tags and can provide detailed knowledge of the 2000 most highly expressed genes in the tissue sample. The SAGE protocols presented are detailed, fully annotated, and tested, and are all written by experienced SAGE researchers from around the world. Part 1 is dedicated to experimental procedures of SAGE and related methods including aRNA LongSAGE, SuperSAGE, DeepSAGE, and GMAT. Part 2 provides methods for extraction and filtration of tags, analysis of ditag populations, and completing statistically correct comparisons of gene expression profiles. Comparative transcriptomics enables scientists to understand the underlying genetics of biological changes such as development, disease, crop yield, and resistance. SAGE analysis is also used to obtain unknown tags, which can be used as gene-specific primers in Rapid Amplification of cDNA Ends (RACE) reactions to generate full-length transcripts for cloning and sequencing. This book will be an indispensable tool for any lab engaged in genetic profiling and comparative transcriptomics, and will help many laboratories to successfully implement tag-based sequencing methods and procedures and obtain comprehensive, useful, and interpretative data.
Download or read book RNA Seq Analysis Methods Applications and Challenges written by Filippo Geraci and published by Frontiers Media SA. This book was released on 2020-06-08 with total page 169 pages. Available in PDF, EPUB and Kindle. Book excerpt:
