| chip sequencing data analysis: Practical Guide to ChIP-seq Data Analysis Borbala Mifsud, Kathi Zarnack, Anaïs F Bardet, 2018-10-26 Chromatin immunoprecipitation sequencing (ChIP-seq), which maps the genome-wide localization patterns of transcription factors and epigenetic marks, is among the most widely used methods in molecular biology. Practical Guide to ChIP-seq Data Analysis will guide readers through the steps of ChIP-seq analysis: from quality control, through peak calling, to downstream analyses. It will help experimental biologists to design their ChIP-seq experiments with the analysis in mind, and to perform the basic analysis steps themselves. It also aims to support bioinformaticians to understand how the data is generated, what the sources of biases are, and which methods are appropriate for different analyses. |
| chip sequencing data analysis: Computational Genomics with R Altuna Akalin, 2020-12-16 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. |
| chip sequencing data analysis: Next-Generation Sequencing Data Analysis Xinkun Wang, 2016-04-06 A Practical Guide to the Highly Dynamic Area of Massively Parallel SequencingThe development of genome and transcriptome sequencing technologies has led to a paradigm shift in life science research and disease diagnosis and prevention. Scientists are now able to see how human diseases and phenotypic changes are connected to DNA mutation, polymorphi |
| chip sequencing data analysis: Chromatin Immunoprecipitation Neus Visa, Antonio Jordán-Pla, 2017-10-14 This up-to-date volume includes protocols that illustrate the broad use of chromatin immunoprecipitation (ChIP) and ChIP-related methods in a variety of biological research areas. The collection also includes protocols designed to improve the performance of ChIP for specific applications. Written in the highly successful Methods in Molecular Biology series format, chapters include introduction to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, as well as tips on troubleshooting and avoiding known pitfalls. Authoritative and practical, Chromatin Immunoprecipitation: Methods and Protocols features techniques, including bioinformatic analysis of ChIP data, will be of interest to a very broad research community in the fields of biochemistry, molecular biology, microbiology, and biomedicine. |
| chip sequencing data analysis: Computational Systems Biology of Cancer Emmanuel Barillot, Laurence Calzone, Philippe Hupe, Jean-Philippe Vert, Andrei Zinovyev, 2012-08-25 The future of cancer research and the development of new therapeutic strategies rely on our ability to convert biological and clinical questions into mathematical models—integrating our knowledge of tumour progression mechanisms with the tsunami of information brought by high-throughput technologies such as microarrays and next-generation sequencing. Offering promising insights on how to defeat cancer, the emerging field of systems biology captures the complexity of biological phenomena using mathematical and computational tools. Novel Approaches to Fighting Cancer Drawn from the authors’ decade-long work in the cancer computational systems biology laboratory at Institut Curie (Paris, France), Computational Systems Biology of Cancer explains how to apply computational systems biology approaches to cancer research. The authors provide proven techniques and tools for cancer bioinformatics and systems biology research. Effectively Use Algorithmic Methods and Bioinformatics Tools in Real Biological Applications Suitable for readers in both the computational and life sciences, this self-contained guide assumes very limited background in biology, mathematics, and computer science. It explores how computational systems biology can help fight cancer in three essential aspects: Categorising tumours Finding new targets Designing improved and tailored therapeutic strategies Each chapter introduces a problem, presents applicable concepts and state-of-the-art methods, describes existing tools, illustrates applications using real cases, lists publically available data and software, and includes references to further reading. Some chapters also contain exercises. Figures from the text and scripts/data for reproducing a breast cancer data analysis are available at www.cancer-systems-biology.net. |
| chip sequencing data analysis: Practical Guide to ChIP-seq Data Analysis Borbala Mifsud, Kathi Zarnack, Anaïs F Bardet, 2018-10-26 Chromatin immunoprecipitation sequencing (ChIP-seq), which maps the genome-wide localization patterns of transcription factors and epigenetic marks, is among the most widely used methods in molecular biology. Practical Guide to ChIP-seq Data Analysis will guide readers through the steps of ChIP-seq analysis: from quality control, through peak calling, to downstream analyses. It will help experimental biologists to design their ChIP-seq experiments with the analysis in mind, and to perform the basic analysis steps themselves. It also aims to support bioinformaticians to understand how the data is generated, what the sources of biases are, and which methods are appropriate for different analyses. |
| chip sequencing data analysis: Deep Sequencing Data Analysis Noam Shomron, 2013-07-20 The new genetic revolution is fuelled by Deep Sequencing (or Next Generation Sequencing) apparatuses which, in essence, read billions of nucleotides per reaction. Effectively, when carefully planned, any experimental question which can be translated into reading nucleic acids can be applied.In Deep Sequencing Data Analysis, expert researchers in the field detail methods which are now commonly used to study the multi-facet deep sequencing data field. These included techniques for compressing of data generated, Chromatin Immunoprecipitation (ChIP-seq), and various approaches for the identification of sequence variants. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of necessary materials and reagents, step-by-step, readily reproducible protocols, and key tips on troubleshooting and avoiding known pitfalls. Authoritative and practical, Deep Sequencing Data Analysis seeks to aid scientists in the further understanding of key data analysis procedures for deep sequencing data interpretation. |
| chip sequencing data analysis: Next-Generation Sequencing and Sequence Data Analysis Kuo Ping Chiu, 2015-11-04 Nucleic acid sequencing techniques have enabled researchers to determine the exact order of base pairs - and by extension, the information present - in the genome of living organisms. Consequently, our understanding of this information and its link to genetic expression at molecular and cellular levels has lead to rapid advances in biology, genetics, biotechnology and medicine. Next-Generation Sequencing and Sequence Data Analysis is a brief primer on DNA sequencing techniques and methods used to analyze sequence data. Readers will learn about recent concepts and methods in genomics such as sequence library preparation, cluster generation for PCR technologies, PED sequencing, genome assembly, exome sequencing, transcriptomics and more. This book serves as a textbook for students undertaking courses in bioinformatics and laboratory methods in applied biology. General readers interested in learning about DNA sequencing techniques may also benefit from the simple format of information presented in the book. |
| chip sequencing data analysis: Next Generation Sequencing Jerzy Kulski, 2016-01-14 Next generation sequencing (NGS) has surpassed the traditional Sanger sequencing method to become the main choice for large-scale, genome-wide sequencing studies with ultra-high-throughput production and a huge reduction in costs. The NGS technologies have had enormous impact on the studies of structural and functional genomics in all the life sciences. In this book, Next Generation Sequencing Advances, Applications and Challenges, the sixteen chapters written by experts cover various aspects of NGS including genomics, transcriptomics and methylomics, the sequencing platforms, and the bioinformatics challenges in processing and analysing huge amounts of sequencing data. Following an overview of the evolution of NGS in the brave new world of omics, the book examines the advances and challenges of NGS applications in basic and applied research on microorganisms, agricultural plants and humans. This book is of value to all who are interested in DNA sequencing and bioinformatics across all fields of the life sciences. |
| chip sequencing data analysis: Field Guidelines for Genetic Experimental Designs in High-Throughput Sequencing Ana M. Aransay, José Luis Lavín Trueba, 2016-06-02 High throughput sequencing (HTS) technologies have conquered the genomics and epigenomics worlds. The applications of HTS methods are wide, and can be used to sequence everything from whole or partial genomes, transcriptomes, non-coding RNAs, ribosome profiling, to single-cell sequencing. Having such diversity of alternatives, there is a demand for information by research scientists without experience in HTS that need to choose the most suitable methodology or combination of platforms and to define their experimental designs to achieve their specific objectives. Field Guidelines for Genetic Experimental Designs in High-Throughput Sequencing aims to collect in a single volume all aspects that should be taken into account when HTS technologies are being incorporated into a research project and the reasons behind them. Moreover, examples of several successful strategies will be analyzed to make the point of the crucial features. This book will be of use to all scientist that are unfamiliar with HTS and want to incorporate such technologies to their research. |
| chip sequencing data analysis: Statistical Analysis of Next Generation Sequencing Data Somnath Datta, Dan Nettleton, 2016-09-17 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. |
| chip sequencing data analysis: Epigenetics Protocols Trygve O. Tollefsbol, 2004-07-23 The field of epigenetics has grown exponentially in the past decade, and a steady flow of exciting discoveries in this area has served to move it to the forefront of molecular biology. Although epigenetics may previously have been considered a peripheral science, recent advances have shown considerable progress in unraveling the many mysteries of nontraditional genetic processes. Given the fast pace of epigenetic discoveries and the groundbreaking nature of these developments, a thorough treatment of the methods in the area seems timely and appropriate and is the goal of Epigenetics Protocols. The scope of epigenetics is vast, and an exhaustive analysis of all of the techniques employed by investigators would be unrealistic. However, this TM volume of Methods in Molecular Biology covers three main areas that should be of greatest interest to epigenetics investigators: (1) techniques related to analysis of chromatin remodeling, such as histone acetylation and methylation; (2) methods in newly developed and especially promising areas of epigenetics such as telomere position effects, quantitative epigenetics, and ADP ribosylation; and (3) an updated analysis of techniques involving DNA methylation and its role in the modification, as well as the maintenance, of chromatin structure. |
| chip sequencing data analysis: Computational Exome and Genome Analysis Peter N. Robinson, Rosario Michael Piro, Marten Jager, 2017-09-13 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. |
| chip sequencing data analysis: Bioinformatics for High Throughput Sequencing Naiara Rodríguez-Ezpeleta, Michael Hackenberg, Ana M. Aransay, 2011-10-26 Next generation sequencing is revolutionizing molecular biology. Owing to this new technology it is now possible to carry out a panoply of experiments at an unprecedented low cost and high speed. These go from sequencing whole genomes, transcriptomes and small non-coding RNAs to description of methylated regions, identification protein – DNA interaction sites and detection of structural variation. The generation of gigabases of sequence information for each of this huge bandwidth of applications in just a few days makes the development of bioinformatics applications for next generation sequencing data analysis as urgent as challenging. |
| chip sequencing data analysis: DNA-Protein Interactions Andrew Arthur Travers, 1993-04-30 The binding of proteins to DNA and the manipulation of DNA by proteins are crucial aspects of the biological role of DNA in the living cell. This book provides a comprehensive and lucid discussion of the molecular interactions involved. |
| chip sequencing data analysis: Hi-C Data Analysis Silvio Bicciato, Francesco Ferrari, 2022-09-04 This volume details a comprehensive set of methods and tools for Hi-C data processing, analysis, and interpretation. Chapters cover applications of Hi-C to address a variety of biological problems, with a specific focus on state-of-the-art computational procedures adopted for the data analysis. 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, Hi-C Data Analysis: Methods and Protocols aims to help computational and molecular biologists working in the field of chromatin 3D architecture and transcription regulation. |
| chip sequencing data analysis: Genome Instability Marco Muzi-Falconi, Grant W Brown, 2017-10-20 This volume presents forty-two methods and protocols to analyze diverse aspects of genome instability. Chapters detail mutagenesis and repair, methods to quantify and analyze the properties of DNA double-strand breaks, profile replication, replication proteins strand-specifically, genome instability, fluorescence microscopic techniques, and genomic and proteomic approaches. 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, Genome Instability: Methods and Protocols aims to provide a comprehensive resource for the discovery and analysis of the proteins and pathways that are critical for stable maintenance of the genome. |
| chip sequencing data analysis: Data Analysis for the Life Sciences with R Rafael A. Irizarry, Michael I. Love, 2016-10-04 This book covers several of the statistical concepts and data analytic skills needed to succeed in data-driven life science research. The authors proceed from relatively basic concepts related to computed p-values to advanced topics related to analyzing highthroughput data. They include the R code that performs this analysis and connect the lines of code to the statistical and mathematical concepts explained. |
| chip sequencing data analysis: Molecular Data Analysis Using R Csaba Ortutay, Zsuzsanna Ortutay, 2017-02-06 This book addresses the difficulties experienced by wet lab researchers with the statistical analysis of molecular biology related data. The authors explain how to use R and Bioconductor for the analysis of experimental data in the field of molecular biology. The content is based upon two university courses for bioinformatics and experimental biology students (Biological Data Analysis with R and High-throughput Data Analysis with R). The material is divided into chapters based upon the experimental methods used in the laboratories. Key features include: • Broad appeal--the authors target their material to researchers in several levels, ensuring that the basics are always covered. • First book to explain how to use R and Bioconductor for the analysis of several types of experimental data in the field of molecular biology. • Focuses on R and Bioconductor, which are widely used for data analysis. One great benefit of R and Bioconductor is that there is a vast user community and very active discussion in place, in addition to the practice of sharing codes. Further, R is the platform for implementing new analysis approaches, therefore novel methods are available early for R users. |
| chip sequencing data analysis: DNA Modifications Alexey Ruzov, Martin Gering, 2020-08-22 This book provides an overview of methods and experimental protocols that are currently used to analyze the presence and abundance of non-canonical DNA nucleotides in different biological systems. Focusing particularly on the newly discovered and less studied DNA modifications that are enzymatically produced and are likely to play specific roles in various biological processes, the volume explores chromatography- and mass spectrometry-based techniques for the detection and quantification of DNA modifications, antibody-based approaches to study their spatial distribution in different cells and tissues, and methods to analyze their genomic distribution with the help of bioinformatics tools that interrogate the corresponding datasets. Written for the highly successful Methods in Molecular Biology series, 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 comprehensive, DNA Modifications: Methods and Protocols serves as an ideal guide to research scientists and PhD students in this rapidly developing discipline, and, thus, will ultimately contribute to deciphering the roles of non-canonical DNA nucleotides in different biological systems. |
| chip sequencing data analysis: Open Source Software in Life Science Research Lee Harland, Mark Forster, 2012-10-31 The free/open source approach has grown from a minor activity to become a significant producer of robust, task-orientated software for a wide variety of situations and applications. To life science informatics groups, these systems present an appealing proposition - high quality software at a very attractive price. Open source software in life science research considers how industry and applied research groups have embraced these resources, discussing practical implementations that address real-world business problems.The book is divided into four parts. Part one looks at laboratory data management and chemical informatics, covering software such as Bioclipse, OpenTox, ImageJ and KNIME. In part two, the focus turns to genomics and bioinformatics tools, with chapters examining GenomicsTools and EBI Atlas software, as well as the practicalities of setting up an 'omics' platform and managing large volumes of data. Chapters in part three examine information and knowledge management, covering a range of topics including software for web-based collaboration, open source search and visualisation technologies for scientific business applications, and specific software such as DesignTracker and Utopia Documents. Part four looks at semantic technologies such as Semantic MediaWiki, TripleMap and Chem2Bio2RDF, before part five examines clinical analytics, and validation and regulatory compliance of free/open source software. Finally, the book concludes by looking at future perspectives and the economics and free/open source software in industry. - Discusses a broad range of applications from a variety of sectors - Provides a unique perspective on work normally performed behind closed doors - Highlights the criteria used to compare and assess different approaches to solving problems |
| chip sequencing data analysis: Finite Mixture and Markov Switching Models Sylvia Frühwirth-Schnatter, 2006-11-24 The past decade has seen powerful new computational tools for modeling which combine a Bayesian approach with recent Monte simulation techniques based on Markov chains. This book is the first to offer a systematic presentation of the Bayesian perspective of finite mixture modelling. The book is designed to show finite mixture and Markov switching models are formulated, what structures they imply on the data, their potential uses, and how they are estimated. Presenting its concepts informally without sacrificing mathematical correctness, it will serve a wide readership including statisticians as well as biologists, economists, engineers, financial and market researchers. |
| chip sequencing data analysis: Fungal Genomics Ronald P. de Vries, Adrian Tsang, Igor V. Grigoriev, 2019-06-21 This volume details protocols covering nearly all aspects of fungal genomics. New and updated chapters guide the reader through experimental genomics, biotechnologies, and the analysis and processing of data. 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 practical, Fungal Genomics : Methods and Protocols, Second Edition aims to ensure successful results in the further study of this vital field. |
| chip sequencing data analysis: Next Steps for Functional Genomics National Academies of Sciences, Engineering, and Medicine, Division on Earth and Life Studies, Board on Life Sciences, 2020-12-18 One of the holy grails in biology is the ability to predict functional characteristics from an organism's genetic sequence. Despite decades of research since the first sequencing of an organism in 1995, scientists still do not understand exactly how the information in genes is converted into an organism's phenotype, its physical characteristics. Functional genomics attempts to make use of the vast wealth of data from -omics screens and projects to describe gene and protein functions and interactions. A February 2020 workshop was held to determine research needs to advance the field of functional genomics over the next 10-20 years. Speakers and participants discussed goals, strategies, and technical needs to allow functional genomics to contribute to the advancement of basic knowledge and its applications that would benefit society. This publication summarizes the presentations and discussions from the workshop. |
| chip sequencing data analysis: Genome Analysis: Current Procedures and Applications Maria S. Poptsova, 2019-04-28 In recent years there have been tremendous achievements made in DNA sequencing technologies and corresponding innovations in data analysis and bioinformatics that have revolutionized the field of genome analysis.In this book, an impressive array of expert authors highlight and review current advances in genome analysis. This volume provides an invaluable, up-to-date and comprehensive overview of the methods currently employed for next-generation sequencing (NGS) data analysis, highlights their problems and limitations, demonstrates the applications and indicates the developing trends in various fields of genome research. The first part of the book is devoted to the methods and applications that arose from, or were significantly advanced by, NGS technologies: the identification of structural variation from DNA-seq data; whole-transcriptome analysis and discovery of small interfering RNAs (siRNAs) from RNA-seq data; motif finding in promoter regions, enhancer prediction and nucleosome sequence code discovery from ChiP-Seq data; identification of methylation patterns in cancer from MeDIP-seq data; transposon identification in NGS data; metagenomics and metatranscriptomics; NGS of viral communities; and causes and consequences of genome instabilities. The second part is devoted to the field of RNA biology with the last three chapters devoted to computational methods of RNA structure prediction including context-free grammar applications.An essential book for everyone involved in sequence data analysis, next-generation sequencing, high-throughput sequencing, RNA structure prediction, bioinformatics and genome analysis. |
| chip sequencing data analysis: Data Mining Techniques for the Life Sciences Oliviero Carugo, Frank Eisenhaber, 2016-08-23 Most life science researchers will agree that biology is not a truly theoretical branch of science. The hype around computational biology and bioinformatics beginning in the nineties of the 20th century was to be short lived (1, 2). When almost no value of practical importance such as the optimal dose of a drug or the three-dimensional structure of an orphan protein can be computed from fundamental principles, it is still more straightforward to determine them experimentally. Thus, experiments and observationsdogeneratetheoverwhelmingpartofinsightsintobiologyandmedicine. The extrapolation depth and the prediction power of the theoretical argument in life sciences still have a long way to go. Yet, two trends have qualitatively changed the way how biological research is done today. The number of researchers has dramatically grown and they, armed with the same protocols, have produced lots of similarly structured data. Finally, high-throu- put technologies such as DNA sequencing or array-based expression profiling have been around for just a decade. Nevertheless, with their high level of uniform data generation, they reach the threshold of totally describing a living organism at the biomolecular level for the first time in human history. Whereas getting exact data about living systems and the sophistication of experimental procedures have primarily absorbed the minds of researchers previously, the weight increasingly shifts to the problem of interpreting accumulated data in terms of biological function and bio- lecular mechanisms. |
| chip sequencing data analysis: Gene Network Inference Alberto Fuente, 2014-01-03 This book presents recent methods for Systems Genetics (SG) data analysis, applying them to a suite of simulated SG benchmark datasets. Each of the chapter authors received the same datasets to evaluate the performance of their method to better understand which algorithms are most useful for obtaining reliable models from SG datasets. The knowledge gained from this benchmarking study will ultimately allow these algorithms to be used with confidence for SG studies e.g. of complex human diseases or food crop improvement. The book is primarily intended for researchers with a background in the life sciences, not for computer scientists or statisticians. |
| chip sequencing data analysis: Genomics and Bioinformatics Tore Samuelsson, 2012-06-07 With the arrival of genomics and genome sequencing projects, biology has been transformed into an incredibly data-rich science. The vast amount of information generated has made computational analysis critical and has increased demand for skilled bioinformaticians. Designed for biologists without previous programming experience, this textbook provides a hands-on introduction to Unix, Perl and other tools used in sequence bioinformatics. Relevant biological topics are used throughout the book and are combined with practical bioinformatics examples, leading students through the process from biological problem to computational solution. All of the Perl scripts, sequence and database files used in the book are available for download at the accompanying website, allowing the reader to easily follow each example using their own computer. Programming examples are kept at an introductory level, avoiding complex mathematics that students often find daunting. The book demonstrates that even simple programs can provide powerful solutions to many complex bioinformatics problems. |
| chip sequencing data analysis: Mixtures Kerrie L. Mengersen, Christian Robert, Mike Titterington, 2011-05-03 This book uses the EM (expectation maximization) algorithm to simultaneously estimate the missing data and unknown parameter(s) associated with a data set. The parameters describe the component distributions of the mixture; the distributions may be continuous or discrete. The editors provide a complete account of the applications, mathematical structure and statistical analysis of finite mixture distributions along with MCMC computational methods, together with a range of detailed discussions covering the applications of the methods and features chapters from the leading experts on the subject. The applications are drawn from scientific discipline, including biostatistics, computer science, ecology and finance. This area of statistics is important to a range of disciplines, and its methodology attracts interest from researchers in the fields in which it can be applied. |
| chip sequencing data analysis: The Myc Gene Laura Soucek, Jonathan Whitfield, 2021-05-23 This second edition provides new and updated chapters detailing recent advances in MYC research and current techniques. Chapters guide readers through protocols on how to express and purify MYC protein, X-ray crystallography, NMR, techniques to study how MYC is modified, apoptosis, senescence, proliferation, metabolic changes, translation, tumorigenesis,reprogramming, and clinical application of MYC studies.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, The Myc Gene: Methods and Protocols, Second Edition aims to ensure successful results in the further study of this vital field. |
| chip sequencing data analysis: Yeast Functional Genomics Frédéric Devaux, 2015-10-20 This volume provides a collection of protocols for the study of DNA-DNA contact maps, replication profiles, transcription rates, RNA secondary structures, protein-RNA interactions, ribosome profiling and quantitative proteomes and metabolomes. Written for the Methods in Molecular Biology series, 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 practical, Yeast Functional Genomics: Methods and Protocols aims to ensure successful results in the further study of this vital field. |
| chip sequencing data analysis: Gene Regulation in Eukaryotes Edgar Wingender, 1993 A much-needed guide through the overwhelming amount of literature in the field. Comprehensive and detailed, this book combines background information with the most recentinsights. It introduces current concepts, emphasizing the transcriptional control of genetic information. Moreover, it links data on the structure of regulatory proteins with basic cellular processes. Both advanced students and experts will find answers to such intriguing questions as: - How are programs of specific gene repertoires activated and controlled? - Which genes drive and control morphogenesis? - Which genes govern tissue-specific tasks? - How do hormones control gene expression in coordinating the activities of different tissues? An abundant number of clearly presented glossary terms facilitates understanding of the biological background. Speacial feature: over 2200 (!) literature references. |
| chip sequencing data analysis: Sample Size Calculations in Clinical Research Shein-Chung Chow, Jun Shao, Hansheng Wang, Yuliya Lokhnygina, 2017-08-15 Praise for the Second Edition: ... this is a useful, comprehensive compendium of almost every possible sample size formula. The strong organization and carefully defined formulae will aid any researcher designing a study. -Biometrics This impressive book contains formulae for computing sample size in a wide range of settings. One-sample studies and two-sample comparisons for quantitative, binary, and time-to-event outcomes are covered comprehensively, with separate sample size formulae for testing equality, non-inferiority, and equivalence. Many less familiar topics are also covered ... – Journal of the Royal Statistical Society Sample Size Calculations in Clinical Research, Third Edition presents statistical procedures for performing sample size calculations during various phases of clinical research and development. A comprehensive and unified presentation of statistical concepts and practical applications, this book includes a well-balanced summary of current and emerging clinical issues, regulatory requirements, and recently developed statistical methodologies for sample size calculation. Features: Compares the relative merits and disadvantages of statistical methods for sample size calculations Explains how the formulae and procedures for sample size calculations can be used in a variety of clinical research and development stages Presents real-world examples from several therapeutic areas, including cardiovascular medicine, the central nervous system, anti-infective medicine, oncology, and women’s health Provides sample size calculations for dose response studies, microarray studies, and Bayesian approaches This new edition is updated throughout, includes many new sections, and five new chapters on emerging topics: two stage seamless adaptive designs, cluster randomized trial design, zero-inflated Poisson distribution, clinical trials with extremely low incidence rates, and clinical trial simulation. |
| chip sequencing data analysis: Gene Mapping, Discovery, and Expression Minou Bina, 2008-02-04 Completion of the sequence of the human genome represents an unpar- leled achievement in the history of biology. The project has produced nearly complete, highly accurate, and comprehensive sequences of genomes of s- eral organisms including human, mouse, drosophila, and yeast. Furthermore, the development of high-throughput technologies has led to an explosion of projects to sequence the genomes of additional organisms including rat, chimp, dog, bee, chicken, and the list is expanding. The nearly completed draft of genomic sequences from numerous species has opened a new era of research in biology and in biomedical sciences. In keeping with the interdisciplinary nature of the new scientific era, the chapters in Gene Mapping, Discovery, and Expression: Methods and Protocols recapitulate the necessity of integration of experimental and computational tools for solving - portant research problems. The general underlying theme of this volume is DNA sequence-based technologies. At one level, the book highlights the importance of databases, genome-browsers, and web-based tools for data access and ana- sis. More specifically, sequencing projects routinely deposit their data in p- licly available databases including GenBank, at the National Center of Biotechnology (NCBI) in the United States; EMBL, maintained by the European Bioinformatics Institute; and DDBJ, the DNA Data Bank of Japan. Currently, several browsers offer facile access to numerous genomic DNA sequences for gene mapping and data retrieval. |
| chip sequencing data analysis: Promoter Associated RNA Sara Napoli, 2018-06-09 This volume is divided in four sections; covering genome wide approaches, techniques for characterize of paRNA structural features are described, selecting pa-RNA, and paRNA therapeutic potential. Chapters describe how siRNAsdirected against paRNAs can be applied in vivo to modulate transcription of important genes controlled by paRNAs. 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, Promoter Associated RNA: Methods and Protocols aims to demonstrate paRNAs as new class of regulatory molecules, to further investigate and value as tools for fine transcriptional tuning. |
| chip sequencing data analysis: Plant Systems Biology Sacha Baginsky, Alisdair R. Fernie, 2007-06-25 This volume aims to provide a timely view of the state-of-the-art in systems biology. The editors take the opportunity to define systems biology as they and the contributing authors see it, and this will lay the groundwork for future studies. The volume is well-suited to both students and researchers interested in the methods of systems biology. Although the focus is on plant systems biology, the proposed material could be suitably applied to any organism. |
| chip sequencing data analysis: Bioinformatics for Comparative Proteomics Cathy H. Wu, Chuming Chen, 2010-11-19 With the rapid development of proteomic technologies in the life sciences and in clinical applications, many bioinformatics methodologies, databases, and software tools have been developed to support comparative proteomics study. In Bioinformatics for Comparative Proteomics, experts in the field highlight the current status, challenges, open problems, and future trends for developing bioinformatics tools and resources for comparative proteomics research in order to deliver a definitive reference providing both the breadth and depth needed on the subject. Structured in three major sections, this detailed volume covers basic bioinformatics frameworks relating to comparative proteomics, bioinformatics databases and tools for proteomics data analysis, and integrated bioinformatics systems and approaches for studying comparative proteomics in the systems biology context. Written for the highly successful Methods in Molecular BiologyTM series, the contributions in this book provide the meticulous, step-by-step description and implementation advice that is crucial for getting optimal results in the lab. Comprehensive and easy-to-use, Bioinformatics for Comparative Proteomics serves all readers who wish to learn about state-of-the-art bioinformatics databases and tools, novel computational methods and future trends in proteomics data analysis, and comparative proteomics in systems biology. |
| chip sequencing data analysis: Chronic Lymphocytic Leukemia Sami Malek, 2018 |
| chip sequencing data analysis: HiC-Pro: an Optimized and Flexible Pipeline for Hi-C Data Processing Oldenburg Oldenburg Press, 2016-01-29 HiC-Pro is an optimized and flexible pipeline for processing Hi-C data from raw reads to normalized contact maps. HiC-Pro maps reads, detects valid ligation products, performs quality controls and generates intra- and inter-chromosomal contact maps. It includes a fast implementation of the iterative correction method and is based on a memory-efficient data format for Hi-C contact maps. In addition, HiC-Pro can use phased genotype data to build allele-specific contact maps. We applied HiC-Pro to different Hi-C datasets, demonstrating its ability to easily process large data in a reasonable time. Source code and documentation are available at http://github.com/nservant/HiC-Pro. |
| chip sequencing data analysis: Next Generation Sequencing and Data Analysis Melanie Kappelmann-Fenzl, 2021-05-04 This textbook provides step-by-step protocols and detailed explanations for RNA Sequencing, ChIP-Sequencing and Epigenetic Sequencing applications. The reader learns how to perform Next Generation Sequencing data analysis, how to interpret and visualize the data, and acquires knowledge on the statistical background of the used software tools. Written for biomedical scientists and medical students, this textbook enables the end user to perform and comprehend various Next Generation Sequencing applications and their analytics without prior understanding in bioinformatics or computer sciences. |
社区 - Chiphell - 分享与交流用户体验
1 day ago · Chiphell - 分享与交流用户体验 电脑 硬件 显卡 内存 硬盘 手机 SSD 机箱 鼠标 键盘 高端 Intel AMD ,Chiphell - 分享与交流用户体验
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电脑 - Chiphell - 分享与交流用户体验
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传说级显卡RTX4090-48G小测 - 电脑讨论(新) - Chiphell - 分享与 …
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华硕H610thin-itx主板供电问题 - 电脑讨论(新) - Chiphell - 分享与 …
Chip一Hell 发表于 2025-1-27 08:25 先整一块板子试一下 我在用同类型一体机板，现在外接的明纬DC55*25 24V11A适配器，您说的那个4P口和DC口是电气并联的，可以理解为外接电源输入口 …
两步解决Windows11 24H2 专业版无法访问局域网共享 - 电脑讨 …
Oct 2, 2024 · 解决过几家公司局域网问题，都是装机商的批量系统权限和策略都不太一样那种。后来发现只用一步就行了，就是去添加windows凭据，用机器名+用户名+密码就行，因为甚至有 …
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May 11, 2025 · 麒麟X90性能估算,新发布的鸿蒙电脑，使用X90芯片有网友已通过cpu的代号查到芯片用的是手机上的9010的内核。
社区 - Chiphell - 分享与交流用户体验
1 day ago · Chiphell - 分享与交流用户体验 电脑 硬件 显卡 内存 硬盘 手机 SSD 机箱 鼠标 键盘 高端 Intel AMD ,Chiphell - 分享与交流用户体验
9070/9070XT 规格确认！304W/220W - 电脑讨论(新) - Chiphell
Feb 21, 2025 · 9070/9070xt 规格确认！304w/220w,amd 已确认 radeon rx 9070 xt 将搭载 2970 mhz 加速频率 与 304w 总板功耗（tbp）而基础版 rx 9070 非 xt 型号的加速频率为 2520 …
电脑 - Chiphell - 分享与交流用户体验
Jun 9, 2025 · 电脑 ,Chiphell - 分享与交流用户体验. 命运真是难以捉摸，就在我以为耗时 3 个月后还是摸不到 5090 FE 时，一时兴起改买了 RTX PRO 6000：RTX 5090 FE 的破壁人 —— …
首页 - Chiphell - 分享与交流用户体验
Chiphell - 分享与交流用户体验 ,Chiphell - 分享与交流用户体验
传说级显卡RTX4090-48G小测 - 电脑讨论(新) - Chiphell - 分享与交 …
Feb 15, 2025 · 传说级显卡RTX4090-48G小测,楼主对50系彻底失去信心之后，在溢价5090D和48G4090之间，决然选择了后者，一不做二不休，闲鱼21500块货拉拉包邮买了一张2小时到 …
群晖2025年新品，包括DS1825+和DS1525+，925+ - 电脑讨论(新) …
Mar 12, 2025 · 群晖2025年新品，包括ds1825+和ds1525+，925+,rt，群晖将在2025年上半年发布ds1825+，我的天啊，终于看到希望了，不知道今年618有没有活动。
电脑讨论(新) - Chiphell - 分享与交流用户体验
1 day ago · 电脑讨论(新)Chiphell - 分享与交流用户体验 ,Chiphell - 分享与交流用户体验
华硕H610thin-itx主板供电问题 - 电脑讨论(新) - Chiphell - 分享与 …
Chip一Hell 发表于 2025-1-27 08:25 先整一块板子试一下 我在用同类型一体机板，现在外接的明纬DC55*25 24V11A适配器，您说的那个4P口和DC口是电气并联的，可以理解为外接电源输入口 …
两步解决Windows11 24H2 专业版无法访问局域网共享 - 电脑讨论
Oct 2, 2024 · 解决过几家公司局域网问题，都是装机商的批量系统权限和策略都不太一样那种。后来发现只用一步就行了，就是去添加windows凭据，用机器名+用户名+密码就行，因为甚至有 …
麒麟X90性能估算 - 电脑讨论(新) - Chiphell - 分享与交流用户体验
May 11, 2025 · 麒麟X90性能估算,新发布的鸿蒙电脑，使用X90芯片有网友已通过cpu的代号查到芯片用的是手机上的9010的内核。
