Author: Basel Abu-Jamous
Publisher: John Wiley & Sons
ISBN: 1118906535
Category : Technology & Engineering
Languages : en
Pages : 451
Book Description
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
Author: Basel Abu-Jamous
Publisher: John Wiley & Sons
ISBN: 1118906535
Category : Technology & Engineering
Languages : en
Pages : 451
Book Description
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
Publisher: John Wiley & Sons
ISBN: 1118906535
Category : Technology & Engineering
Languages : en
Pages : 451
Book Description
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
Author: Basel Abu-Jamous
Publisher: John Wiley & Sons
ISBN: 1118906551
Category : Technology & Engineering
Languages : en
Pages : 451
Book Description
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
Publisher: John Wiley & Sons
ISBN: 1118906551
Category : Technology & Engineering
Languages : en
Pages : 451
Book Description
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
Author: Basel Abu Jamous
Publisher:
ISBN: 9781118906545
Category : MATHEMATICS
Languages : en
Pages :
Book Description
Publisher:
ISBN: 9781118906545
Category : MATHEMATICS
Languages : en
Pages :
Book Description
Computational Methods for Single-Cell Data Analysis
Author: Guo-Cheng Yuan
Publisher: Humana Press
ISBN: 9781493990566
Category : Science
Languages : en
Pages : 271
Book Description
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.
Publisher: Humana Press
ISBN: 9781493990566
Category : Science
Languages : en
Pages : 271
Book Description
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
Author: Rabinarayan Satpathy
Publisher: John Wiley & Sons
ISBN: 111978560X
Category : Computers
Languages : en
Pages : 433
Book Description
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.
Publisher: John Wiley & Sons
ISBN: 111978560X
Category : Computers
Languages : en
Pages : 433
Book Description
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.
Integrating Omics Data
Author: George Tseng
Publisher: Cambridge University Press
ISBN: 1107069114
Category : Mathematics
Languages : en
Pages : 497
Book Description
Tutorial chapters by leaders in the field introduce state-of-the-art methods to handle information integration problems of omics data.
Publisher: Cambridge University Press
ISBN: 1107069114
Category : Mathematics
Languages : en
Pages : 497
Book Description
Tutorial chapters by leaders in the field introduce state-of-the-art methods to handle information integration problems of omics data.
The Wiley Handbook of Human Computer Interaction Set
Author: Kent Norman
Publisher: John Wiley & Sons
ISBN: 1118977270
Category : Psychology
Languages : de
Pages : 2263
Book Description
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.
Publisher: John Wiley & Sons
ISBN: 1118977270
Category : Psychology
Languages : de
Pages : 2263
Book Description
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.
Algorithms for Computational Biology
Author: Adrian-Horia Dediu
Publisher: Springer
ISBN: 3319079530
Category : Computers
Languages : en
Pages : 285
Book Description
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.
Publisher: Springer
ISBN: 3319079530
Category : Computers
Languages : en
Pages : 285
Book Description
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.
Bayesian Statistics and New Generations
Author: Raffaele Argiento
Publisher: Springer Nature
ISBN: 3030306119
Category : Mathematics
Languages : en
Pages : 184
Book Description
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.
Publisher: Springer Nature
ISBN: 3030306119
Category : Mathematics
Languages : en
Pages : 184
Book Description
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.
Gene Quantification
Author: Francois Ferre
Publisher: Springer Science & Business Media
ISBN: 1461241642
Category : Medical
Languages : en
Pages : 379
Book Description
Geneticists and molecular biologists have been interested in quantifying genes and their products for many years and for various reasons (Bishop, 1974). Early molecular methods were based on molecular hybridization, and were devised shortly after Marmur and Doty (1961) first showed that denaturation of the double helix could be reversed - that the process of molecular reassociation was exquisitely sequence dependent. Gillespie and Spiegelman (1965) developed a way of using the method to titrate the number of copies of a probe within a target sequence in which the target sequence was fixed to a membrane support prior to hybridization with the probe - typically a RNA. Thus, this was a precursor to many of the methods still in use, and indeed under development, today. Early examples of the application of these methods included the measurement of the copy numbers in gene families such as the ribosomal genes and the immunoglo bulin family. Amplification of genes in tumors and in response to drug treatment was discovered by this method. In the same period, methods were invented for estimating gene num bers based on the kinetics of the reassociation process - the so-called Cot analysis. This method, which exploits the dependence of the rate of reassociation on the concentration of the two strands, revealed the presence of repeated sequences in the DNA of higher eukaryotes (Britten and Kohne, 1968). An adaptation to RNA, Rot analysis (Melli and Bishop, 1969), was used to measure the abundance of RNAs in a mixed population.
Publisher: Springer Science & Business Media
ISBN: 1461241642
Category : Medical
Languages : en
Pages : 379
Book Description
Geneticists and molecular biologists have been interested in quantifying genes and their products for many years and for various reasons (Bishop, 1974). Early molecular methods were based on molecular hybridization, and were devised shortly after Marmur and Doty (1961) first showed that denaturation of the double helix could be reversed - that the process of molecular reassociation was exquisitely sequence dependent. Gillespie and Spiegelman (1965) developed a way of using the method to titrate the number of copies of a probe within a target sequence in which the target sequence was fixed to a membrane support prior to hybridization with the probe - typically a RNA. Thus, this was a precursor to many of the methods still in use, and indeed under development, today. Early examples of the application of these methods included the measurement of the copy numbers in gene families such as the ribosomal genes and the immunoglo bulin family. Amplification of genes in tumors and in response to drug treatment was discovered by this method. In the same period, methods were invented for estimating gene num bers based on the kinetics of the reassociation process - the so-called Cot analysis. This method, which exploits the dependence of the rate of reassociation on the concentration of the two strands, revealed the presence of repeated sequences in the DNA of higher eukaryotes (Britten and Kohne, 1968). An adaptation to RNA, Rot analysis (Melli and Bishop, 1969), was used to measure the abundance of RNAs in a mixed population.