Genome Clustering

Author : Alexander Bolshoy,Zeev Volkovich,Valery Kirzhner,Zeev Barzily
Publisher : Springer Science & Business Media
Page : 234 pages
File Size : 49,8 Mb
Release : 2010-05-19
Category : Computers
ISBN : 9783642129513

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Genome Clustering by Alexander Bolshoy,Zeev Volkovich,Valery Kirzhner,Zeev Barzily Pdf

Knighting in sequence biology Edward N. Trifonov Genome classification, construction of phylogenetic trees, became today a major approach in studying evolutionary relatedness of various species in their vast - versity. Although the modern genome clustering delivers the trees which are very similar to those generated by classical means, and basic terminology is the same, the phenotypic traits and habitats are not anymore the playground for the classi- cation. The sequence space is the playground now. The phenotypic traits are - placed by sequence characteristics, “words”, in particular. Matter-of-factually, the phenotype and genotype merged, to confusion of both classical and modern p- logeneticists. Accordingly, a completely new vocabulary of stringology, information theory and applied mathematics took over. And a new brand of scientists emerged – those who do know the math and, simultaneously, (do?) know biology. The book is written by the authors of this new brand. There is no way to test their literacy in biology, as no biologist by training would even try to enter into the elite circle of those who masters their almost occult language. But the army of - formaticians, formal linguists, mathematicians humbly (or aggressively) longing to join modern biology, got an excellent introduction to the field of genome cl- tering, written by the team of their kin.

Author : Jason T. L. Wang,Cathy H. Wu,Paul P. Wang
Publisher : World Scientific
Page : 266 pages
File Size : 49,9 Mb
Release : 2003
Category : Science
ISBN : 9789812382573

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Computational Biology and Genome Informatics by Jason T. L. Wang,Cathy H. Wu,Paul P. Wang Pdf

This book contains articles written by experts on a wide range of topics that are associated with the analysis and management of biological information at the molecular level. It contains chapters on RNA and protein structure analysis, DNA computing, sequence mapping, genome comparison, gene expression data mining, metabolic network modeling, and phyloinformatics. The important work of some representative researchers in bioinformatics is brought together for the first time in one volume. The topic is treated in depth and is related to, where applicable, other emerging technologies such as data mining and visualization. The goal of the book is to introduce readers to the principle techniques of bioinformatics in the hope that they will build on them to make new discoveries of their own. Contents: Exploring RNA Intermediate Conformations with the Massively Parallel Genetic Algorithm; Introduction to Self-Assembling DNA Nanostructures for Computation and Nanofabrication; Mapping Sequence to Rice FPC; Graph Theoretic Sequence Clustering Algorithms and their Applications to Genome Comparison; The Protein Information Resource for Functional Genomics and Proteomics; High-Grade Ore for Data Mining in 3D Structures; Protein Classification: A Geometric Hashing Approach; Interrelated Clustering: An Approach for Gene Expression Data Analysis; Creating Metabolic Network Models Using Text Mining and Expert Knowledge; Phyloinformatics and Tree Networks. Readership: Molecular biologists who rely on computers and mathematical scientists with interests in biology.

Author : Altuna Akalin
Publisher : CRC Press
Page : 462 pages
File Size : 40,7 Mb
Release : 2020-12-16
Category : Mathematics
ISBN : 9781498781862

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Computational Genomics with R by Altuna Akalin Pdf

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.

Author : Toshiyuki Nagata,Satoshi Tabata
Publisher : Springer Science & Business Media
Page : 292 pages
File Size : 53,5 Mb
Release : 2003-04-14
Category : Technology & Engineering
ISBN : 3540427287

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Brassicas and Legumes From Genome Structure to Breeding by Toshiyuki Nagata,Satoshi Tabata Pdf

Genome sequence studies have become more and more important for plant breeding. Brassicas and Legumes: From Genome Structure to Breeding comprises 16 chapters and presents both an overview and the latest results of this rapidly expanding field. Topics covered include: genome analysis of a flowering plant, Arabidopsis thaliana; the sequence of the Arabidopsis genome as a tool for comparative structural genomics in Brassicaceae; application of molecular markers in Brassica coenospecies; the molecular genetic basis of flowering time variation in Brassica species; quantitative trait loci for clubroot resistance in Brassica oleracea; structural differences of S locus between Brassica oleracea and Brassica rapa; Brassica and legume chromosomes; sequence analysis of the Lotus japonicus genome; introduction of an early flowering accession ‘Miyakojima’ MG-20 to molecular genetics in Lotus japonicus; genetic linkage map of the model legume Lotus japonicus; construction of a high quality genome library of Lotus japonicus; genome analysis of Mesorhizobium loti: a symbiotic partner to Lotus japonicus; molecular linkage map of the model legume Medicago truncatula; genetic mapping of seed and nodule protein markers in diploid alfalfa (Medicago sativa); mapping the chickpea (Cicer arietinum) genome: localization of fungal resistance genes in interspecific crosses.

Author : Kefei Chen,Li Ma
Publisher : Frontiers Media SA
Page : 147 pages
File Size : 42,9 Mb
Release : 2023-12-11
Category : Science
ISBN : 9782832540619

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From Agriculture Genome to Phenome: Genome-Wide Association, Prediction and Selection by Kefei Chen,Li Ma Pdf

The advances in “omics” technologies have enabled unprecedented progress in agricultural and biological sciences. The synergy of high-performance computing, high throughput omics approaches, and high dimensional phenotyping data with high spatial and temporal resolution have demonstrated the capacity to enhance our understanding of biological mechanisms but also to provide powerful insights into dissecting the genetic basis of complex traits with agricultural and economical importance. Genome-wide association study (GWAS) has become a useful approach to identify mutations that underlie diseases and complex traits and has provided important insights in exploring genetic profiles. However, it is less suitable for quantitative traits influenced by a large number of genes with small effects. In addition, false discoveries are a major concern and can be partially attributed to population structure. Genomic selection holds the promise to overcome the limitations by using whole-genome information to predict the genetic merits of phenotypes. It has been a powerful tool for predicting the breeding values of candidates for selection in breeding populations. One of the challenges of genomic prediction of breeding values with large-p-with-small-n regressions is to develop robust and efficient approaches that accurately predict phenotypic traits as functions of genotypic and environmental inputs. In addition, the integration of multi-omics data in phenotypic prediction would offer the opportunity to understand the flow of information that underlies the phenotypic traits.

Author : James Womack
Publisher : John Wiley & Sons
Page : 285 pages
File Size : 49,5 Mb
Release : 2012-03-16
Category : Science
ISBN : 9781118301708

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Bovine Genomics by James Womack Pdf

The genetic information being unlocked by advances in genomic and high throughput technologies is rapidly revolutionizing our understanding of developmental processes in bovine species. This information is allowing researchers unprecedented insight into the genetic basis of key traits. Bovine Genomics is the first book to bring together and synthesize the information learned through the bovine genome sequencing project and look at its practical application to cattle and dairy production. Bovine Genomics opens with foundational chapters on the domestication of cattle and traditional Mendelian genetics. Building on these chapters, coverage rapidly moves to quantitative genetics and the advances of whole genome technologies. Significant coverage is given to such topics as epigenetics, mapping quantitative trail loci, genome-wide association studies and genomic selection in cattle breeding. The book is a valuable synthesis of the field written by a global team of leading researchers. Providing wide-ranging coverage of the topic, Bovine Genomic, is an essential guide to the field. The basic and applied science will be of use to researchers, breeders, and advanced students.

Author : Edda Klipp,Charles Delisi,Minoru Kanehisa,Satoru Miyano,Scott Mohr,Iwona Wallach
Publisher : Imperial College Press
Page : 215 pages
File Size : 42,8 Mb
Release : 2010-01-18
Category : Science
ISBN : 9781908977991

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Genome Informatics 2009: Genome Informatics Series Vol. 22 - Proceedings Of The 9th Annual International Workshop On Bioinformatics And Systems Biology (Ibsb 2009) by Edda Klipp,Charles Delisi,Minoru Kanehisa,Satoru Miyano,Scott Mohr,Iwona Wallach Pdf

This volume contains 17 peer-reviewed papers based on the presentations at the 9th Annual International Workshop on Bioinformatics and Systems Biology (IBSB 2009) held at the Life Science Engineering Building of Boston University from July 27 to 29, 2009. This workshop started in 2001 as a platform for doctoral students and young researchers to present and discuss their research results and approaches in bioinformatics and systems biology. It is part of a collaborative educational program involving leading institutions and leaders committed to the following institutions and programs:Boston University Graduate Program in BioinformaticsCharité - Universitätsmedizin BerlinFreie Universität BerlinGlobal COE Program — Center of Education and Research for Advanced Genome-Based Medicine, University of TokyoThe International Research Training Group (IRTG) Genomics and Systems Biology of Molecular NetworksInternational Research and Training Program on Bioinformatics and Systems Biology, Kyoto University Bioinformatics CenterMax-Delbrück Center for Molecular Medicine in BerlinMax Planck Institute for Molecular Genetics in BerlinMax Planck Institute of Molecular Plant Physiology in Potsdam/a

Author : Debmalya Barh,Siomar C. Soares,Sandeep Tiwari,Vasco Ariston De Car Azevedo
Publisher : Academic Press
Page : 476 pages
File Size : 45,9 Mb
Release : 2020-03-06
Category : Science
ISBN : 9780128170779

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Pan-genomics: Applications, Challenges, and Future Prospects by Debmalya Barh,Siomar C. Soares,Sandeep Tiwari,Vasco Ariston De Car Azevedo Pdf

Pan-genomics: Applications, Challenges, and Future Prospects covers current approaches, challenges and future prospects of pan-genomics. The book discusses bioinformatics tools and their applications and focuses on bacterial comparative genomics in order to leverage the development of precise drugs and treatments for specific organisms. The book is divided into three sections: the first, an "overview of pan-genomics and common approaches, brings the main concepts and current approaches on pan-genomics research; the second, “case studies in pan-genomics, thoroughly discusses twelve case, and the last, “current approaches and future prospects in pan-multiomics , encompasses the developments on omics studies to be applied on bacteria related studies. This book is a valuable source for bioinformaticians, genomics researchers and several members of biomedical field interested in understanding further bacterial organisms and their relationship to human health. Covers the entire spectrum of pangenomics, highlighting the use of specific approaches, case studies and future perspectives Discusses current bioinformatics tools and strategies for exploiting pangenomics data Presents twelve case studies with different organisms in order to provide the audience with real examples of pangenomics applicability

Author : Edward R. Dougherty
Publisher : Hindawi Publishing Corporation
Page : 456 pages
File Size : 49,7 Mb
Release : 2005
Category : DNA microarrays
ISBN : 9789775945075

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Genomic Signal Processing and Statistics by Edward R. Dougherty Pdf

Recent advances in genomic studies have stimulated synergetic research and development in many cross-disciplinary areas. Processing the vast genomic data, especially the recent large-scale microarray gene expression data, to reveal the complex biological functionality, represents enormous challenges to signal processing and statistics. This perspective naturally leads to a new field, genomic signal processing (GSP), which studies the processing of genomic signals by integrating the theory of signal processing and statistics. Written by an international, interdisciplinary team of authors, this invaluable edited volume is accessible to students just entering this emergent field, and to researchers, both in academia and in industry, in the fields of molecular biology, engineering, statistics, and signal processing. The book provides tutorial-level overviews and addresses the specific needs of genomic signal processing students and researchers as a reference book. The book aims to address current genomic challenges by exploiting potential synergies between genomics, signal processing, and statistics, with special emphasis on signal processing and statistical tools for structural and functional understanding of genomic data. The first part of this book provides a brief history of genomic research and a background introduction from both biological and signal-processing/statistical perspectives, so that readers can easily follow the material presented in the rest of the book. In what follows, overviews of state-of-the-art techniques are provided. We start with a chapter on sequence analysis, and follow with chapters on feature selection, classification, and clustering of microarray data. We then discuss the modeling, analysis, and simulation of biological regulatory networks, especially gene regulatory networks based on Boolean and Bayesian approaches. Visualization and compression of gene data, and supercomputer implementation of genomic signal processing systems are also treated. Finally, we discuss systems biology and medical applications of genomic research as well as the future trends in genomic signal processing and statistics research.

Author : Alexander Bolshoy,Zeev Volkovich,Valery Kirzhner
Publisher : Unknown
Page : 240 pages
File Size : 40,7 Mb
Release : 2010-09-08
Category : Electronic
ISBN : 3642129536

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Genome Clustering by Alexander Bolshoy,Zeev Volkovich,Valery Kirzhner Pdf

Author : Marcelino Pérez de la Vega,Marta Santalla,Frédéric Marsolais
Publisher : Springer
Page : 295 pages
File Size : 48,8 Mb
Release : 2017-12-20
Category : Science
ISBN : 9783319635262

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The Common Bean Genome by Marcelino Pérez de la Vega,Marta Santalla,Frédéric Marsolais Pdf

This book provides insights into the genetics and the latest advances in genomics research on the common bean, offering a timely overview of topics that are pertinent for future developments in legume genomics. The common bean (Phaseolus vulgaris L.) is the most important grain legume crop for food consumption worldwide, as well as a model for legume research, and the availability of the genome sequence has completely changed the paradigm of the ongoing research on the species. Key topics covered include the numerous genetic and genomic resources, available tools, the identified genes and quantitative trait locus (QTL) identified, and there is a particular emphasis on domestication. It is a valuable resource for students and researchers interested in the genetics and genomics of the common bean and legumes in general.

Author : Rafael R. de la Haba,André Antunes,Brian P. Hedlund
Publisher : Frontiers Media SA
Page : 431 pages
File Size : 53,7 Mb
Release : 2022-08-31
Category : Science
ISBN : 9782889769315

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Extremophiles: Microbial Genomics and Taxogenomics by Rafael R. de la Haba,André Antunes,Brian P. Hedlund Pdf

Author : Ashish Gupta
Publisher : Packt Publishing Ltd
Page : 131 pages
File Size : 53,8 Mb
Release : 2015-10-08
Category : Computers
ISBN : 9781783284443

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Apache Mahout Clustering Designs by Ashish Gupta Pdf

Explore clustering algorithms used with Apache Mahout About This Book Use Mahout for clustering datasets and gain useful insights Explore the different clustering algorithms used in day-to-day work A practical guide to create and evaluate your own clustering models using real world data sets Who This Book Is For This book is for developers who want to try out clustering on large datasets using Mahout. It will also be useful for those users who don't have background in Mahout, but have knowledge of basic programming and are familiar with basics of machine learning and clustering. It will be helpful if you know about clustering techniques with some other tool. What You Will Learn Explore clustering algorithms and cluster evaluation techniques Learn different types of clustering and distance measuring techniques Perform clustering on your data using K-Means clustering Discover how canopy clustering is used as pre-process step for K-Means Use the Fuzzy K-Means algorithm in Apache Mahout Implement Streaming K-Means clustering in Mahout Learn Spectral K-Means clustering implementation of Mahout In Detail As more and more organizations are discovering the use of big data analytics, interest in platforms that provide storage, computation, and analytic capabilities has increased. Apache Mahout caters to this need and paves the way for the implementation of complex algorithms in the field of machine learning to better analyse your data and get useful insights into it. Starting with the introduction of clustering algorithms, this book provides an insight into Apache Mahout and different algorithms it uses for clustering data. It provides a general introduction of the algorithms, such as K-Means, Fuzzy K-Means, StreamingKMeans, and how to use Mahout to cluster your data using a particular algorithm. You will study the different types of clustering and learn how to use Apache Mahout with real world data sets to implement and evaluate your clusters. This book will discuss about cluster improvement and visualization using Mahout APIs and also explore model-based clustering and topic modelling using Dirichlet process. Finally, you will learn how to build and deploy a model for production use. Style and approach This book is a hand's-on guide with examples using real-world datasets. Each chapter begins by explaining the algorithm in detail and follows up with showing how to use mahout for that algorithm using example data-sets.

Author : Nicos Maglaveras,Ioanna Chouvarda,Vassilis Koutkias,Rüdiger Brause
Publisher : Springer Science & Business Media
Page : 507 pages
File Size : 51,7 Mb
Release : 2006-11-27
Category : Medical
ISBN : 9783540680635

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Biological and Medical Data Analysis by Nicos Maglaveras,Ioanna Chouvarda,Vassilis Koutkias,Rüdiger Brause Pdf

This book constitutes the refereed proceedings of the 7th International Symposium on Biological and Medical Data Analysis, ISBMDA 2006, held in Thessaloniki, Greece, December 2006. Coverage in this volume includes functional genomics, sequence analysis, biomedical models, information modeling, biomedical signal processing, biomedical image analysis, biomedical data analysis, as well as decision support systems and diagnostic tools.

Author : Glenn Tesler,Dannie Durand
Publisher : Springer Science & Business Media
Page : 203 pages
File Size : 49,6 Mb
Release : 2007-08-31
Category : Science
ISBN : 9783540749592

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Comparative Genomics by Glenn Tesler,Dannie Durand Pdf

This book constitutes the refereed proceedings of the 5th RECOMB Comparative Genomics Satellite Workshop, RECOMB-CG 2007, held in San Diego, CA, USA, in September 2007. The 14 revised full papers presented address a broad variety of aspects and components of the field of comparative genomics, ranging from quantitative discoveries about genome structure to algorithms for comparative inference to theorems on the complexity of computational problems required for genome comparison.