Integrative Cluster Analysis in Bioinformatics
Integrative Cluster Analysis in Bioinformatics

Author: Basel Abu-Jamous

Publisher: John Wiley & Sons

Published: 2015-06-15

Total Pages: 451

ISBN-13: 1118906535

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Clustering techniques are increasingly being put to use in the analysis of high-throughput biological datasets. Novel computational techniques to analyse high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. This book details the complete pathway of cluster analysis, from the basics of molecular biology to the generation of biological knowledge. The book also presents the latest clustering methods and clustering validation, thereby offering the reader a comprehensive review of clustering analysis in bioinformatics from the fundamentals through to state-of-the-art techniques and applications. Key Features: Offers a contemporary review of clustering methods and applications in the field of bioinformatics, with particular emphasis on gene expression analysis Provides an excellent introduction to molecular biology with computer scientists and information engineering researchers in mind, laying out the basic biological knowledge behind the application of clustering analysis techniques in bioinformatics Explains the structure and properties of many types of high-throughput datasets commonly found in biological studies Discusses how clustering methods and their possible successors would be used to enhance the pace of biological discoveries in the future Includes a companion website hosting a selected collection of codes and links to publicly available datasets

Integrative Cluster Analysis in Bioinformatics
Integrative Cluster Analysis in Bioinformatics

Author: Basel Abu-Jamous

Publisher: John Wiley & Sons

Published: 2015-04-16

Total Pages: 451

ISBN-13: 1118906551

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Clustering techniques are increasingly being put to use in the analysis of high-throughput biological datasets. Novel computational techniques to analyse high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. This book details the complete pathway of cluster analysis, from the basics of molecular biology to the generation of biological knowledge. The book also presents the latest clustering methods and clustering validation, thereby offering the reader a comprehensive review of clustering analysis in bioinformatics from the fundamentals through to state-of-the-art techniques and applications. Key Features: Offers a contemporary review of clustering methods and applications in the field of bioinformatics, with particular emphasis on gene expression analysis Provides an excellent introduction to molecular biology with computer scientists and information engineering researchers in mind, laying out the basic biological knowledge behind the application of clustering analysis techniques in bioinformatics Explains the structure and properties of many types of high-throughput datasets commonly found in biological studies Discusses how clustering methods and their possible successors would be used to enhance the pace of biological discoveries in the future Includes a companion website hosting a selected collection of codes and links to publicly available datasets

Computational Methods for Single-Cell Data Analysis
Computational Methods for Single-Cell Data Analysis

Author: Guo-Cheng Yuan

Publisher: Humana Press

Published: 2019-02-14

Total Pages: 271

ISBN-13: 9781493990566

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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.

Data Analytics in Bioinformatics
Data Analytics in Bioinformatics

Author: Rabinarayan Satpathy

Publisher: John Wiley & Sons

Published: 2021-01-20

Total Pages: 433

ISBN-13: 111978560X

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Machine learning techniques are increasingly being used to address problems in computational biology and bioinformatics. Novel machine learning computational techniques to analyze high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. Machine learning techniques such as Markov models, support vector machines, neural networks, and graphical models have been successful in analyzing life science data because of their capabilities in handling randomness and uncertainty of data noise and in generalization. Machine Learning in Bioinformatics compiles recent approaches in machine learning methods and their applications in addressing contemporary problems in bioinformatics approximating classification and prediction of disease, feature selection, dimensionality reduction, gene selection and classification of microarray data and many more.

The Wiley Handbook of Human Computer Interaction Set
The Wiley Handbook of Human Computer Interaction Set

Author: Kent Norman

Publisher: John Wiley & Sons

Published: 2017-12-28

Total Pages: 2263

ISBN-13: 1118977270

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In der Vergangenheit war die Mensch-Computer-Interaktion (Human-Computer Interaction) das Privileg einiger weniger. Heute ist Computertechnologie weit verbreitet, allgegenwärtig und global. Arbeiten und Lernen erfolgen über den Computer. Private und kommerzielle Systeme arbeiten computergestützt. Das Gesundheitswesen wird neu erfunden. Navigation erfolgt interaktiv. Unterhaltung kommt aus dem Computer. Als Antwort auf immer leistungsfähigere Systeme sind im Bereich der Mensch-Computer-Interaktion immer ausgeklügeltere Theorien und Methodiken entstanden. The Wiley Handbook of Human-Computer Interaction bietet einen Überblick über all diese Entwicklungen und untersucht die vielen verschiedenen Aspekte der Mensch-Computer-Interaktion und hat den Wert menschlicher Erfahrungen, die über Technologie stehen, ganzheitlich im Blick.

Bayesian Statistics and New Generations
Bayesian Statistics and New Generations

Author: Raffaele Argiento

Publisher: Springer Nature

Published: 2019-11-21

Total Pages: 184

ISBN-13: 3030306119

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This book presents a selection of peer-reviewed contributions to the fourth Bayesian Young Statisticians Meeting, BAYSM 2018, held at the University of Warwick on 2-3 July 2018. The meeting provided a valuable opportunity for young researchers, MSc students, PhD students, and postdocs interested in Bayesian statistics to connect with the broader Bayesian community. The proceedings offer cutting-edge papers on a wide range of topics in Bayesian statistics, identify important challenges and investigate promising methodological approaches, while also assessing current methods and stimulating applications. The book is intended for a broad audience of statisticians, and demonstrates how theoretical, methodological, and computational aspects are often combined in the Bayesian framework to successfully tackle complex problems.

Algorithms for Computational Biology
Algorithms for Computational Biology

Author: Adrian-Horia Dediu

Publisher: Springer

Published: 2014-06-07

Total Pages: 285

ISBN-13: 3319079530

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This book constitutes the refereed proceedings of the First International Conference, AlCoB 2014, held in July 2014 in Tarragona, Spain. The 20 revised full papers were carefully reviewed and selected from 39 submissions. The scope of AlCoB includes topics of either theoretical or applied interest, namely: exact sequence analysis, approximate sequence analysis, pairwise sequence alignment, multiple sequence alignment, sequence assembly, genome rearrangement, regulatory motif finding, phylogeny reconstruction, phylogeny comparison, structure prediction, proteomics: molecular pathways, interaction networks, transcriptomics: splicing variants, isoform inference and quantification, differential analysis, next-generation sequencing: population genomics, metagenomics, metatranscriptomics, microbiome analysis, systems biology.

Ancestral Sequence Reconstruction
Ancestral Sequence Reconstruction

Author: David A Liberles

Publisher: Oxford University Press

Published: 2007-05-31

Total Pages: 267

ISBN-13: 0199299188

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Ancestral sequence reconstruction is a technique of growing importance in molecular evolutionary biology and comparative genomics. As a powerful tool for testing evolutionary and ecological hypotheses, as well as uncovering the link between sequence and molecular phenotype, there are potential applications in a range of fields.Ancestral Sequence Reconstruction starts with a historical overview of the field, before discussing the potential applications in drug discovery and the pharmaceutical industry. This is followed by a section on computational methodology, which provides a detailed discussion of the available methods for reconstructing ancestral sequences (including their advantages, disadvantages, and potential pitfalls). Purely computational applications of the technique are then covered, including wholeproteome reconstruction. Further chapters provide a detailed discussion on taking computationally reconstructed sequences and synthesizing them in the laboratory. The book concludes with a description of the scientific questions where experimental ancestral sequence reconstruction has been utilized toprovide insights and inform future research.This research level text provides a first synthesis of the theories, methodologies and applications associated with ancestral sequence recognition, while simultaneously addressing many of the hot topics in the field. It will be of interest and use to both graduate students and researchers in the fields of molecular biology, molecular evolution, and evolutionary bioinformatics.

RNA Sequence, Structure, and Function: Computational and Bioinformatic Methods
RNA Sequence, Structure, and Function: Computational and Bioinformatic Methods

Author: Jan Gorodkin

Publisher: Humana

Published: 2014-03-18

Total Pages: 0

ISBN-13: 9781627037082

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The existence of genes for RNA molecules not coding for proteins (ncRNAs) has been recognized since the 1950's, but until recently, aside from the critically important ribosomal and transfer RNA genes, most focus has been on protein coding genes. However, a long series of striking discoveries, from RNA's ability to carry out catalytic function, to discovery of riboswitches, microRNAs and other ribo-regulators performing critical tasks in essentially all living organisms, has created a burgeoning interest in this primordial component of the biosphere. However, the structural characteristics and evolutionary constraints on RNA molecules are very different from those of proteins, necessitating development of a completely new suite of informatic tools to address these challenges. In RNA Sequence, Structure, Function: Computational and Bioinformatic Methods, expert researchers in the field describe a substantial and relevant fraction of these methodologies from both practical and computational/algorithmic perspectives. Focusing on both of these directions addresses both the biologist interested in knowing more about RNA bioinformatics as well as the bioinformaticist interested in more detailed aspects of the algorithms. Written in the highly successful Methods in Molecular Biology series format, the chapters include the kind of detailed description and implementation advice that is crucial for getting optimal results. Thorough and intuitive, RNA Sequence, Structure, Function: Computational and Bioinformatic Methods aids scientists in continuing to study key methods and principles of RNA bioinformatics.