Computational Analysis of Gene Expression Data

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Publisher :
ISBN 13 : 9783832226060
Total Pages : 164 pages
Book Rating : 4.2/5 (26 download)

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Book Synopsis Computational Analysis of Gene Expression Data by : Alexander Zien

Download or read book Computational Analysis of Gene Expression Data written by Alexander Zien and published by . This book was released on 2004 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Computational Analysis of Gene Expression Data

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Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (822 download)

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Book Synopsis Computational Analysis of Gene Expression Data by : Gráinne Kerr

Download or read book Computational Analysis of Gene Expression Data written by Gráinne Kerr and published by . This book was released on 2009 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Computational Methods for Single-Cell Data Analysis

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Publisher : Humana Press
ISBN 13 : 9781493990566
Total Pages : 271 pages
Book Rating : 4.9/5 (95 download)

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Book Synopsis Computational Methods for Single-Cell Data Analysis by : Guo-Cheng Yuan

Download or read book Computational Methods for Single-Cell Data Analysis written by Guo-Cheng Yuan and published by Humana Press. This book was released on 2019-02-14 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: This detailed book provides state-of-art computational approaches to further explore the exciting opportunities presented by single-cell technologies. Chapters each detail a computational toolbox aimed to overcome a specific challenge in single-cell analysis, such as data normalization, rare cell-type identification, and spatial transcriptomics analysis, all with a focus on hands-on implementation of computational methods for analyzing experimental 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 cutting-edge, Computational Methods for Single-Cell Data Analysis aims to cover a wide range of tasks and serves as a vital handbook for single-cell data analysis.

Computational Methods for the Analysis of Genomic Data and Biological Processes

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Publisher : MDPI
ISBN 13 : 3039437712
Total Pages : 222 pages
Book Rating : 4.0/5 (394 download)

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Book Synopsis Computational Methods for the Analysis of Genomic Data and Biological Processes by : Francisco A. Gómez Vela

Download or read book Computational Methods for the Analysis of Genomic Data and Biological Processes written by Francisco A. Gómez Vela and published by MDPI. This book was released on 2021-02-05 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent decades, new technologies have made remarkable progress in helping to understand biological systems. Rapid advances in genomic profiling techniques such as microarrays or high-performance sequencing have brought new opportunities and challenges in the fields of computational biology and bioinformatics. Such genetic sequencing techniques allow large amounts of data to be produced, whose analysis and cross-integration could provide a complete view of organisms. As a result, it is necessary to develop new techniques and algorithms that carry out an analysis of these data with reliability and efficiency. This Special Issue collected the latest advances in the field of computational methods for the analysis of gene expression data, and, in particular, the modeling of biological processes. Here we present eleven works selected to be published in this Special Issue due to their interest, quality, and originality.

Gene Expression Data Analysis

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Publisher : CRC Press
ISBN 13 : 1000425738
Total Pages : 379 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Gene Expression Data Analysis by : Pankaj Barah

Download or read book Gene Expression Data Analysis written by Pankaj Barah and published by CRC Press. This book was released on 2021-11-21 with total page 379 pages. Available in PDF, EPUB and Kindle. Book excerpt: Development of high-throughput technologies in molecular biology during the last two decades has contributed to the production of tremendous amounts of data. Microarray and RNA sequencing are two such widely used high-throughput technologies for simultaneously monitoring the expression patterns of thousands of genes. Data produced from such experiments are voluminous (both in dimensionality and numbers of instances) and evolving in nature. Analysis of huge amounts of data toward the identification of interesting patterns that are relevant for a given biological question requires high-performance computational infrastructure as well as efficient machine learning algorithms. Cross-communication of ideas between biologists and computer scientists remains a big challenge. Gene Expression Data Analysis: A Statistical and Machine Learning Perspective has been written with a multidisciplinary audience in mind. The book discusses gene expression data analysis from molecular biology, machine learning, and statistical perspectives. Readers will be able to acquire both theoretical and practical knowledge of methods for identifying novel patterns of high biological significance. To measure the effectiveness of such algorithms, we discuss statistical and biological performance metrics that can be used in real life or in a simulated environment. This book discusses a large number of benchmark algorithms, tools, systems, and repositories that are commonly used in analyzing gene expression data and validating results. This book will benefit students, researchers, and practitioners in biology, medicine, and computer science by enabling them to acquire in-depth knowledge in statistical and machine-learning-based methods for analyzing gene expression data. Key Features: An introduction to the Central Dogma of molecular biology and information flow in biological systems A systematic overview of the methods for generating gene expression data Background knowledge on statistical modeling and machine learning techniques Detailed methodology of analyzing gene expression data with an example case study Clustering methods for finding co-expression patterns from microarray, bulkRNA, and scRNA data A large number of practical tools, systems, and repositories that are useful for computational biologists to create, analyze, and validate biologically relevant gene expression patterns Suitable for multidisciplinary researchers and practitioners in computer science and biological sciences

On the Computational Analysis of Gene Expression Microarray Data

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Publisher :
ISBN 13 : 9789521211058
Total Pages : 55 pages
Book Rating : 4.2/5 (11 download)

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Book Synopsis On the Computational Analysis of Gene Expression Microarray Data by : T. Aittokallio

Download or read book On the Computational Analysis of Gene Expression Microarray Data written by T. Aittokallio and published by . This book was released on 2003 with total page 55 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Computational Text Analysis

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Publisher : OUP Oxford
ISBN 13 : 0191513776
Total Pages : 312 pages
Book Rating : 4.1/5 (915 download)

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Book Synopsis Computational Text Analysis by : Soumya Raychaudhuri

Download or read book Computational Text Analysis written by Soumya Raychaudhuri and published by OUP Oxford. This book was released on 2006-01-26 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book brings together the two disparate worlds of computational text analysis and biology and presents some of the latest methods and applications to proteomics, sequence analysis and gene expression data. Modern genomics generates large and comprehensive data sets but their interpretation requires an understanding of a vast number of genes, their complex functions, and interactions. Keeping up with the literature on a single gene is a challenge itself-for thousands of genes it is simply. impossible. Here, Soumya Raychaudhuri presents the techniques and algorithms needed to access and utilize the vast scientific text, i.e. methods that automatically read the literature on all the genes. Including background chapters on the necessary biology, statistics and genomics, in addition to practical examples of interpreting many different types of modern experiments, this book is ideal for students and researchers in computational biology, bioinformatics, genomics, statistics and computer science

Next Generation Sequencing

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Publisher : BoD – Books on Demand
ISBN 13 : 9535122401
Total Pages : 466 pages
Book Rating : 4.5/5 (351 download)

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Book Synopsis Next Generation Sequencing by : Jerzy Kulski

Download or read book Next Generation Sequencing written by Jerzy Kulski and published by BoD – Books on Demand. This book was released on 2016-01-14 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Computational Genome Analysis

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Publisher : Springer Science & Business Media
ISBN 13 : 0387288074
Total Pages : 542 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis Computational Genome Analysis by : Richard C. Deonier

Download or read book Computational Genome Analysis written by Richard C. Deonier and published by Springer Science & Business Media. This book was released on 2005-12-27 with total page 542 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the foundations of key problems in computational molecular biology and bioinformatics. It focuses on computational and statistical principles applied to genomes, and introduces the mathematics and statistics that are crucial for understanding these applications. The book features a free download of the R software statistics package and the text provides great crossover material that is interesting and accessible to students in biology, mathematics, statistics and computer science. More than 100 illustrations and diagrams reinforce concepts and present key results from the primary literature. Exercises are given at the end of chapters.

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.

Computational Analysis of Sage Data

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Publisher : LAP Lambert Academic Publishing
ISBN 13 : 9783659201417
Total Pages : 104 pages
Book Rating : 4.2/5 (14 download)

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Book Synopsis Computational Analysis of Sage Data by : Seeja K. R.

Download or read book Computational Analysis of Sage Data written by Seeja K. R. and published by LAP Lambert Academic Publishing. This book was released on 2012-08 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt: In post genomic era, with the availability of the large number of genome databases the focus of research has shifted from sequencing to eliciting knowledge from these databases. Data mining is a collection of techniques for discovering previously unknown, valid and useful patterns from large databases. This book gives insight into an application of a data mining technique, called association rule mining, in analyzing Serial Analysis of Gene Expression (SAGE) data. SAGE is a sequencing technique used for measuring the expression levels of genes. Traditional association rule mining algorithms are not suitable for mining gene expression data due to its wide structure. This book contains the description of a specialized association rule mining algorithm, called GeneExpMiner, for SAGE Data analysis. It also contains an application of the association rule mining, where the algorithm is applied to SAGE data, for identifying the co-regulated signature genes. Some open problems which can be considered for further research in this area is also provided at the conclusion. This book is intended to research scholars in the area of computational biology or bioinformatics.

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.

A Computational System for Automated Meta-analysis of Gene Expression Data

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Publisher :
ISBN 13 :
Total Pages : 103 pages
Book Rating : 4.:/5 (1 download)

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Book Synopsis A Computational System for Automated Meta-analysis of Gene Expression Data by : Cory Bryce Giles

Download or read book A Computational System for Automated Meta-analysis of Gene Expression Data written by Cory Bryce Giles and published by . This book was released on 2017 with total page 103 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Molecular Infection Biology

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Publisher : Wiley-Spektrum
ISBN 13 :
Total Pages : 370 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Molecular Infection Biology by : Jörg Hinrich Hacker

Download or read book Molecular Infection Biology written by Jörg Hinrich Hacker and published by Wiley-Spektrum. This book was released on 2002-10-03 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive volume focuses on molecular methods and principles of prokaryotic and eukaryotic pathogens. The authors present the molecular and cellular aspects by focusing on the interactions between pathogenic microorganisms and their hosts. The publication begins with an overview of the most important and dangerous causative agents of infectious diseases. Next are discussions of how microbial "weapons," pathogenicity factors, protein secretion machines, and surface variation systems work, presenting the molecular and genetic methods that are used by scientists for their discovery and analysis. Furthermore, infectious diseases are discussed in light of the newly formed research areas of evolutionary and cellular microbiology and genomics. Future aspects on diagnostic techniques, therapy, and vaccine development are also presented.

Computational Analysis of Sequence Elements Involved in the Regulation of Gene Expression

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Publisher :
ISBN 13 :
Total Pages : 196 pages
Book Rating : 4.:/5 (234 download)

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Book Synopsis Computational Analysis of Sequence Elements Involved in the Regulation of Gene Expression by : Gila Lithwick

Download or read book Computational Analysis of Sequence Elements Involved in the Regulation of Gene Expression written by Gila Lithwick and published by . This book was released on 2006 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Computational Exome and Genome Analysis

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Publisher : CRC Press
ISBN 13 : 1498775993
Total Pages : 575 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis Computational Exome and Genome Analysis by : Peter N. Robinson

Download or read book Computational Exome and Genome Analysis written by Peter N. Robinson and published by CRC Press. This book was released on 2017-09-13 with total page 575 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Computational Methods for the Analysis of Genomic Data and Biological Processes

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Publisher :
ISBN 13 : 9783039437726
Total Pages : 222 pages
Book Rating : 4.4/5 (377 download)

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Book Synopsis Computational Methods for the Analysis of Genomic Data and Biological Processes by : Francisco A. Gómez Vela

Download or read book Computational Methods for the Analysis of Genomic Data and Biological Processes written by Francisco A. Gómez Vela and published by . This book was released on 2021 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent decades, new technologies have made remarkable progress in helping to understand biological systems. Rapid advances in genomic profiling techniques such as microarrays or high-performance sequencing have brought new opportunities and challenges in the fields of computational biology and bioinformatics. Such genetic sequencing techniques allow large amounts of data to be produced, whose analysis and cross-integration could provide a complete view of organisms. As a result, it is necessary to develop new techniques and algorithms that carry out an analysis of these data with reliability and efficiency. This Special Issue collected the latest advances in the field of computational methods for the analysis of gene expression data, and, in particular, the modeling of biological processes. Here we present eleven works selected to be published in this Special Issue due to their interest, quality, and originality.