Contributions to the Statistical and Computational Modeling of DNA Transcription Regulation

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ISBN 13 :
Total Pages : 208 pages
Book Rating : 4.:/5 (9 download)

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Book Synopsis Contributions to the Statistical and Computational Modeling of DNA Transcription Regulation by : Andre Luis Martins

Download or read book Contributions to the Statistical and Computational Modeling of DNA Transcription Regulation written by Andre Luis Martins and published by . This book was released on 2014 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: Transcription is a fundamental and tightly regulated process in living cells and a key step in the expression of the information contained in DNA. A wide variety of experimental assays have been developed that enable genome-wide analysis of the features of transcription and transcription regulation. We present statistical analysis combining both large existing datasets and new experimental assays to explore three aspects of transcription regulation: (i) determinants of transcription factor binding intensity, (ii) characterization of transcription initiation regions at both promoters and enhancers and (iii) unsupervised identification of transcription units. Transcription factor binding intensity is affected by both DNA sequence and local chromatin landscape. We aimed to disentangle these influences by combining PB-seq (a new experimental approach developed by Michael Guertin) with existing modENCODE data in the study of Drosophila Heat Shock Factor (HSF). PB-seq enabled the estimation of the genome-wide binding energy landscape in the absence of chromatin. It further allowed the development of a statistical model to predict the departure of in-vivo binding intensities (from ChIPseq) from the naked chromatin binding intensities (from PB-seq), based on covariates describing the local pre heat shock chromatin environment. We found that DNase I hypersensitivity and tetra-acetylation of H4 were the most influential covariates. Furthermore DNase I hypersensitivity could also be largely recapitulated from the remaining covariates. Lastly, PB-seq data was applied to develop an unbiased model of HSF binding sequences, which revealed distinct biophysical properties of the HSF/HSE interaction and a previously unrecognized substructure within the HSE. Transcription initiation regions at promoters and enhancers have conventionally been treated separately, although they share many features in mammals. We examined all transcription initiation sites, for both stable and unstable transcripts, using GRO-cap (a new experimental assay developed by Leighton Core). Statistical modeling and analysis of this data, and its contrast with existing ENCODE datasets, reveal a common architecture of initiation at both promoters and enhancers. This common architecture features tightly spaced (110 bp) divergent initiation with similar frequencies of core-promoter sequence elements, highly-positioned flanking nucleosomes, and two modes of TF binding. Transcript elongation stability, a feature determined after transcription initiation, provides a more fundamental distinction between promoters and enhancers than the relative abundance of histone modifications and the presence of TFs or co-activators. These results support a unified model of transcription initiation at both promoters and enhancers. Finally, we turn to the identification of transcription units from nascent RNA assays (GRO-seq and PRO-seq). Although existing annotations focus on stable RNA transcripts (cleavage and poly-Adenylation point), transcription extends beyond the cleavage site. As such, the transcription process can potentially influence surrounding regions. We improve on previous work on the detection of transcription units by obtaining an unsupervised method that does not depend on RNA product annotations. We use these results to examine post polyAdenylation extension and cross-strand RNA polymerase collision effects.

Computational and Statistical Approaches to Genomics

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Publisher : Springer Science & Business Media
ISBN 13 : 0387262881
Total Pages : 426 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis Computational and Statistical Approaches to Genomics by : Wei Zhang

Download or read book Computational and Statistical Approaches to Genomics written by Wei Zhang and published by Springer Science & Business Media. This book was released on 2007-12-26 with total page 426 pages. Available in PDF, EPUB and Kindle. Book excerpt: The second edition of this book adds eight new contributors to reflect a modern cutting edge approach to genomics. It contains the newest research results on genomic analysis and modeling using state-of-the-art methods from engineering, statistics, and genomics. These tools and models are then applied to real biological and clinical problems. The book’s original seventeen chapters are also updated to provide new initiatives and directions.

Modeling Transcriptional Regulation

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Publisher : Humana
ISBN 13 : 9781071615362
Total Pages : 307 pages
Book Rating : 4.6/5 (153 download)

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Book Synopsis Modeling Transcriptional Regulation by : SHAHID MUKHTAR

Download or read book Modeling Transcriptional Regulation written by SHAHID MUKHTAR and published by Humana. This book was released on 2022-07-27 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides methods and techniques used in construction of global transcriptional regulatory networks in diverse systems, various layers of gene regulation and mathematical as well as computational modeling of transcriptional gene regulation. 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, Modeling Transcriptional Regulation: Methods and Protocols aims to provide an in depth understanding of new techniques in transcriptional gene regulation for specialized audience.

Frontiers in Computational and Systems Biology

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Publisher : Springer Science & Business Media
ISBN 13 : 1849961964
Total Pages : 411 pages
Book Rating : 4.8/5 (499 download)

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Book Synopsis Frontiers in Computational and Systems Biology by : Jianfeng Feng

Download or read book Frontiers in Computational and Systems Biology written by Jianfeng Feng and published by Springer Science & Business Media. This book was released on 2010-06-14 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biological and biomedical studies have entered a new era over the past two decades thanks to the wide use of mathematical models and computational approaches. A booming of computational biology, which sheerly was a theoretician’s fantasy twenty years ago, has become a reality. Obsession with computational biology and theoretical approaches is evidenced in articles hailing the arrival of what are va- ously called quantitative biology, bioinformatics, theoretical biology, and systems biology. New technologies and data resources in genetics, such as the International HapMap project, enable large-scale studies, such as genome-wide association st- ies, which could potentially identify most common genetic variants as well as rare variants of the human DNA that may alter individual’s susceptibility to disease and the response to medical treatment. Meanwhile the multi-electrode recording from behaving animals makes it feasible to control the animal mental activity, which could potentially lead to the development of useful brain–machine interfaces. - bracing the sheer volume of genetic, genomic, and other type of data, an essential approach is, ?rst of all, to avoid drowning the true signal in the data. It has been witnessed that theoretical approach to biology has emerged as a powerful and st- ulating research paradigm in biological studies, which in turn leads to a new - search paradigm in mathematics, physics, and computer science and moves forward with the interplays among experimental studies and outcomes, simulation studies, and theoretical investigations.

Applying Integrative Computational Models to Study the Evolution of Gene Regulation

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ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (774 download)

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Book Synopsis Applying Integrative Computational Models to Study the Evolution of Gene Regulation by : Dan Xie

Download or read book Applying Integrative Computational Models to Study the Evolution of Gene Regulation written by Dan Xie and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Gene regulatory networks dynamically control the expression levels of all the genes, and are the keys in explaining various phenotypes and biological processes. The advance of high-throughput measurement technology, such as microarray and next-generation sequencing, enabled us to globally scrutinize various cell properties related to gene regulation and build statistical models to make quantitative predictions. The evolutionary process has left all kinds of traces in the current biological systems. The study of the evolution of gene regulatory networks in comparable cell types across species is an efficient method to unravel such evolutionary traces and help us to better understand the regulatory mechanism. The two main themes of my research are: analysing various "omics" data in the evolutionary context to identify conservation and changes in gene regulatory networks; and building computational models to incorporate different "omics" data for the annotation of genomes and prediction of evolution in gene regulation. The second chapter of my thesis described a computational algorithm for de novo prediction of transcription factor binding site motifs in multiple species. The algorithm, named "GibbsModule", uses three information sources to improve the prediction power, which are 1)co-expressed genes sharing the same set of motifs; 2)binding sites co-localizing to form modules; and 3)the conservation for the use of motifs across species. We developed a Gibbs sampling procedure to incorporate the three information sources. GibbsModule out-performed the existing algorithms on several synthetic and real datasets. When applied to study the binding regions of KLF in embryonic stem cells, GibbsModule discovered a new functional motif. We also used ChIP followed by qPCR to demonstrate that the binding affinity of GibbsModule predicted binding sites are stronger than non-predicted motifs. Both genome sequence and gene expression carry information about gene regulation. Therefore, we can learn more about gene regulatory networks by jointly analysing sequence and expression data. In the third chapter of my thesis, we first introduced a comparative study of the pre-implantation process of embryos in three mammalian species: human, mouse, and cow. We measured time course expression profiles of the embryos during the early development, and analysed them together with genome sequence data and ChIP-seq data. We observed a large portion of changed homologous gene expression, suggesting a prevalent rewiring of gene regulation. We associated the changes of gene expression with different types of cis-changes on the genome sequences. Especially, we found about 10% of species specific transposons are carrying multiple functional binding sites, which are likely to explain the evolution of gene expression. The second part of this chapter presented a phylogenetic model that incorporated the change of motif use and gene expression to infer the rewiring of gene regulatory networks. Epi-genetic modifications, including histone modifications and DNA methylation, are known to be associated with gene regulation. In chapter four, we studied the evolution of epi-genomes in pluripotent stem cells of human, mice, and pigs. We observed the conservation of epi-genomes in different categories of genomic regions. We found the evidence of positive and negative selections on the evolution of epi-genomes. Using linear regression models, the evolution of epi-genomes can largely explain the evolution of gene expression. In the second part of this chapter, we introduced a statistical model to describe the evolution of genomes considering both the DNA sequences and epi-genetic modifications. Based on the evolutionary model, we improved the current alignment algorithm with the information of epi-genetic modification distributions.

Computational Methods for Finding Regulatory DNA Motifs Using Sequence Characteristics and Positional Preferences

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ISBN 13 :
Total Pages : 382 pages
Book Rating : 4.:/5 (474 download)

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Book Synopsis Computational Methods for Finding Regulatory DNA Motifs Using Sequence Characteristics and Positional Preferences by : Kannan Tharakaraman

Download or read book Computational Methods for Finding Regulatory DNA Motifs Using Sequence Characteristics and Positional Preferences written by Kannan Tharakaraman and published by . This book was released on 2008 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: Many biologically active regions of a genome can be discovered by searching for small sequence patterns, or "motifs." A class of motifs of great interest in biology corresponds to sites bound by gene regulatory proteins. The shortness and degeneracy of these sites have, however, frustrated standard sequence-based, motif discovery methods. Moreover, as classical experiments in Molecular Biology have shown, a binding site for a regulatory protein can assume different biological functions in different promoter regions, rendering standard methods unsuitable for motif classification. Previous studies have shown that the binding sites for some regulatory proteins have positional preferences with respect to the transcription start site. Making use of the precise transcription start site locations, this thesis describes computational methods to detect binding sites based on their positional and nucleotide preferences. Three different methods of this type are described: (1) an enumerative statistical test, related to gapless BLAST statistics, that detects octanucleotides that are unusually clustered with respect to the transcription start site in promoter sequences, (2) a Gibbs-sampler program that can use the results generated by the statistic (mentioned in 1) to anchor a multiple alignment on any set of positions thought to contribute to a common binding site, and (3) a statistical method to detect clusters of previously defined motifs in promoter sequences anchored on the transcription start site. Extensions to the Gibbs sampler program including a post-processing step, a Markov background model and a Bayesian positional model are also described. Examples from datasets containing known binding sites revealed that positional information lends better retrieval accuracy. In silico validation of the motifs using gene expression data and functional similarity data demonstrated that some binding sites can have two different roles in transcription regulation (activation or repression), depending on where they are positioned with respect to the transcription start site. The results from this thesis broaden our understanding of positional control in gene regulation, and illustrate the significance of incorporating positional information in motif discovery methods. All the tools developed in this study have been made available for download via the World Wide Web.

Computational Genomics with R

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Publisher : CRC Press
ISBN 13 : 1498781861
Total Pages : 462 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis Computational Genomics with R by : Altuna Akalin

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.

Genomic Regulatory Systems

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Publisher : Elsevier
ISBN 13 : 0080525598
Total Pages : 274 pages
Book Rating : 4.0/5 (85 download)

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Book Synopsis Genomic Regulatory Systems by : Eric H. Davidson

Download or read book Genomic Regulatory Systems written by Eric H. Davidson and published by Elsevier. This book was released on 2001-01-24 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: The interaction between biology and evolution has been the subject of great interest in recent years. Because evolution is such a highly debated topic, a biologically oriented discussion will appeal not only to scientists and biologists but also to the interested lay person. This topic will always be a subject of controversy and therefore any breaking information regarding it is of great interest.The author is a recognized expert in the field of developmental biology and has been instrumental in elucidating the relationship between biology and evolution. The study of evolution is of interest to many different kinds of people and Genomic Regulatory Systems: In Development and Evolution is written at a level that is very easy to read and understand even for the nonscientist. * Contents Include* Regulatory Hardwiring: A Brief Overview of the Genomic Control Apparatus and Its Causal Role in Development and Evolution * Inside the Cis-Regulatory Module: Control Logic and How the Regulatory Environment Is Transduced into Spatial Patterns of Gene Expression* Regulation of Direct Cell-Type Specification in Early Development* The Secret of the Bilaterians: Abstract Regulatory Design in Building Adult Body Parts* Changes That Make New Forms: Gene Regulatory Systems and the Evolution of Body Plans

Computational Stem Cell Biology

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Publisher : Humana
ISBN 13 : 9781493992232
Total Pages : 0 pages
Book Rating : 4.9/5 (922 download)

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Book Synopsis Computational Stem Cell Biology by : Patrick Cahan

Download or read book Computational Stem Cell Biology written by Patrick Cahan and published by Humana. This book was released on 2019-05-07 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume details methods and protocols to further the study of stem cells within the computational stem cell biology (CSCB) field. Chapters are divided into four sections covering the theory and practice of modeling of stem cell behavior, analyzing single cell genome-scale measurements, reconstructing gene regulatory networks, and metabolomics. 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, Computational Stem Cell Biology: Methods and Protocols will be an invaluable guide to researchers as they explore stem cells from the perspective of computational biology.

Bayesian Inference for Gene Expression and Proteomics

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Publisher : Cambridge University Press
ISBN 13 : 052186092X
Total Pages : 437 pages
Book Rating : 4.5/5 (218 download)

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Book Synopsis Bayesian Inference for Gene Expression and Proteomics by : Kim-Anh Do

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.

Gene Regulation in Eukaryotes

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Publisher : Wiley-Blackwell
ISBN 13 :
Total Pages : 452 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Gene Regulation in Eukaryotes by : Edgar Wingender

Download or read book Gene Regulation in Eukaryotes written by Edgar Wingender and published by Wiley-Blackwell. This book was released on 1993 with total page 452 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

NETLAB

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Publisher : Springer Science & Business Media
ISBN 13 : 9781852334406
Total Pages : 444 pages
Book Rating : 4.3/5 (344 download)

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Book Synopsis NETLAB by : Ian Nabney

Download or read book NETLAB written by Ian Nabney and published by Springer Science & Business Media. This book was released on 2002 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: Getting the most out of neural networks and related data modelling techniques is the purpose of this book. The text, with the accompanying Netlab toolbox, provides all the necessary tools and knowledge. Throughout, the emphasis is on methods that are relevant to the practical application of neural networks to pattern analysis problems. All parts of the toolbox interact in a coherent way, and implementations and descriptions of standard statistical techniques are provided so that they can be used as benchmarks against which more sophisticated algorithms can be evaluated. Plenty of examples and demonstration programs illustrate the theory and help the reader understand the algorithms and how to apply them.

Statistical Analysis of Next Generation Sequencing Data

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Publisher : Springer
ISBN 13 : 3319072129
Total Pages : 438 pages
Book Rating : 4.3/5 (19 download)

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Book Synopsis Statistical Analysis of Next Generation Sequencing Data by : Somnath Datta

Download or read book Statistical Analysis of Next Generation Sequencing Data written by Somnath Datta and published by Springer. This book was released on 2014-07-03 with total page 438 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Transcriptional Regulation: Molecules, Involved Mechanisms and Misregulation

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Publisher : MDPI
ISBN 13 : 3039212656
Total Pages : 358 pages
Book Rating : 4.0/5 (392 download)

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Book Synopsis Transcriptional Regulation: Molecules, Involved Mechanisms and Misregulation by : Amelia Casamassimi

Download or read book Transcriptional Regulation: Molecules, Involved Mechanisms and Misregulation written by Amelia Casamassimi and published by MDPI. This book was released on 2019-07-30 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a printed edition of the Special Issue Transcriptional Regulation: Molecules, Involved Mechanisms and Misregulation that was published in IJMS

Next Steps for Functional Genomics

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Publisher : National Academies Press
ISBN 13 : 0309676738
Total Pages : 201 pages
Book Rating : 4.3/5 (96 download)

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Book Synopsis Next Steps for Functional Genomics by : National Academies of Sciences, Engineering, and Medicine

Download or read book Next Steps for Functional Genomics written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2020-12-18 with total page 201 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Genomic Control Process

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Publisher : Academic Press
ISBN 13 : 0124047467
Total Pages : 461 pages
Book Rating : 4.1/5 (24 download)

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Book Synopsis Genomic Control Process by : Isabelle S. Peter

Download or read book Genomic Control Process written by Isabelle S. Peter and published by Academic Press. This book was released on 2015-01-21 with total page 461 pages. Available in PDF, EPUB and Kindle. Book excerpt: Genomic Control Process explores the biological phenomena around genomic regulatory systems that control and shape animal development processes, and which determine the nature of evolutionary processes that affect body plan. Unifying and simplifying the descriptions of development and evolution by focusing on the causality in these processes, it provides a comprehensive method of considering genomic control across diverse biological processes. This book is essential for graduate researchers in genomics, systems biology and molecular biology seeking to understand deep biological processes which regulate the structure of animals during development. Covers a vast area of current biological research to produce a genome oriented regulatory bioscience of animal life Places gene regulation, embryonic and postembryonic development, and evolution of the body plan in a unified conceptual framework Provides the conceptual keys to interpret a broad developmental and evolutionary landscape with precise experimental illustrations drawn from contemporary literature Includes a range of material, from developmental phenomenology to quantitative and logic models, from phylogenetics to the molecular biology of gene regulation, from animal models of all kinds to evidence of every relevant type Demonstrates the causal power of system-level understanding of genomic control process Conceptually organizes a constellation of complex and diverse biological phenomena Investigates fundamental developmental control system logic in diverse circumstances and expresses these in conceptual models Explores mechanistic evolutionary processes, illuminating the evolutionary consequences of developmental control systems as they are encoded in the genome

Statistical Modeling and Machine Learning for Molecular Biology

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Publisher : CRC Press
ISBN 13 : 1482258625
Total Pages : 270 pages
Book Rating : 4.4/5 (822 download)

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Book Synopsis Statistical Modeling and Machine Learning for Molecular Biology by : Alan Moses

Download or read book Statistical Modeling and Machine Learning for Molecular Biology written by Alan Moses and published by CRC Press. This book was released on 2017-01-06 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: Molecular biologists are performing increasingly large and complicated experiments, but often have little background in data analysis. The book is devoted to teaching the statistical and computational techniques molecular biologists need to analyze their data. It explains the big-picture concepts in data analysis using a wide variety of real-world molecular biological examples such as eQTLs, ortholog identification, motif finding, inference of population structure, protein fold prediction and many more. The book takes a pragmatic approach, focusing on techniques that are based on elegant mathematics yet are the simplest to explain to scientists with little background in computers and statistics.