Computational Methods for Predicting Post-Translational Modification Sites

Computational Methods for Predicting Post-Translational Modification Sites

Author: Dukka B. KC

Publisher: Springer Nature

Published: 2022-06-13

Total Pages: 337

ISBN-13: 1071623176

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This volume describes computational approaches to predict multitudes of PTM sites. Chapters describe in depth approaches on algorithms, state-of-the-art Deep Learning based approaches, hand-crafted features, physico-chemical based features, issues related to obtaining negative training, sequence-based features, and structure-based features. Written in the format of the highly successful Methods in Molecular Biology series, each chapter includes an introduction to the topic, lists necessary materials and reagents, includes tips on troubleshooting and known pitfalls, and step-by-step, readily reproducible protocols. Authoritative and cutting-edge, Authoritative and cutting-edge, Computational Methods for Predicting Post-Translational Modification Sites aims to be a useful guide for researchers who are interested in the field of PTM site prediction.


Book Synopsis Computational Methods for Predicting Post-Translational Modification Sites by : Dukka B. KC

Download or read book Computational Methods for Predicting Post-Translational Modification Sites written by Dukka B. KC and published by Springer Nature. This book was released on 2022-06-13 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume describes computational approaches to predict multitudes of PTM sites. Chapters describe in depth approaches on algorithms, state-of-the-art Deep Learning based approaches, hand-crafted features, physico-chemical based features, issues related to obtaining negative training, sequence-based features, and structure-based features. Written in the format of the highly successful Methods in Molecular Biology series, each chapter includes an introduction to the topic, lists necessary materials and reagents, includes tips on troubleshooting and known pitfalls, and step-by-step, readily reproducible protocols. Authoritative and cutting-edge, Authoritative and cutting-edge, Computational Methods for Predicting Post-Translational Modification Sites aims to be a useful guide for researchers who are interested in the field of PTM site prediction.

Data Mining Techniques for the Life Sciences

Data Mining Techniques for the Life Sciences

Author: Oliviero Carugo

Publisher: Humana

Published: 2016-08-23

Total Pages: 407

ISBN-13: 9781493956883

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Most life science researchers will agree that biology is not a truly theoretical branch of science. The hype around computational biology and bioinformatics beginning in the nineties of the 20th century was to be short lived (1, 2). When almost no value of practical importance such as the optimal dose of a drug or the three-dimensional structure of an orphan protein can be computed from fundamental principles, it is still more straightforward to determine them experimentally. Thus, experiments and observationsdogeneratetheoverwhelmingpartofinsightsintobiologyandmedicine. The extrapolation depth and the prediction power of the theoretical argument in life sciences still have a long way to go. Yet, two trends have qualitatively changed the way how biological research is done today. The number of researchers has dramatically grown and they, armed with the same protocols, have produced lots of similarly structured data. Finally, high-throu- put technologies such as DNA sequencing or array-based expression profiling have been around for just a decade. Nevertheless, with their high level of uniform data generation, they reach the threshold of totally describing a living organism at the biomolecular level for the first time in human history. Whereas getting exact data about living systems and the sophistication of experimental procedures have primarily absorbed the minds of researchers previously, the weight increasingly shifts to the problem of interpreting accumulated data in terms of biological function and bio- lecular mechanisms.


Book Synopsis Data Mining Techniques for the Life Sciences by : Oliviero Carugo

Download or read book Data Mining Techniques for the Life Sciences written by Oliviero Carugo and published by Humana. This book was released on 2016-08-23 with total page 407 pages. Available in PDF, EPUB and Kindle. Book excerpt: Most life science researchers will agree that biology is not a truly theoretical branch of science. The hype around computational biology and bioinformatics beginning in the nineties of the 20th century was to be short lived (1, 2). When almost no value of practical importance such as the optimal dose of a drug or the three-dimensional structure of an orphan protein can be computed from fundamental principles, it is still more straightforward to determine them experimentally. Thus, experiments and observationsdogeneratetheoverwhelmingpartofinsightsintobiologyandmedicine. The extrapolation depth and the prediction power of the theoretical argument in life sciences still have a long way to go. Yet, two trends have qualitatively changed the way how biological research is done today. The number of researchers has dramatically grown and they, armed with the same protocols, have produced lots of similarly structured data. Finally, high-throu- put technologies such as DNA sequencing or array-based expression profiling have been around for just a decade. Nevertheless, with their high level of uniform data generation, they reach the threshold of totally describing a living organism at the biomolecular level for the first time in human history. Whereas getting exact data about living systems and the sophistication of experimental procedures have primarily absorbed the minds of researchers previously, the weight increasingly shifts to the problem of interpreting accumulated data in terms of biological function and bio- lecular mechanisms.

Developability of Biotherapeutics

Developability of Biotherapeutics

Author: Sandeep Kumar

Publisher: CRC Press

Published: 2015-11-18

Total Pages: 312

ISBN-13: 1482246155

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Biopharmaceuticals are emerging as frontline medicines to combat several life-threatening and chronic diseases. However, such medicines are expensive to develop and produce on a commercial scale, contributing to rising healthcare costs. Developability of Biotherapeutics: Computational Approaches describes applications of computational and molecular


Book Synopsis Developability of Biotherapeutics by : Sandeep Kumar

Download or read book Developability of Biotherapeutics written by Sandeep Kumar and published by CRC Press. This book was released on 2015-11-18 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biopharmaceuticals are emerging as frontline medicines to combat several life-threatening and chronic diseases. However, such medicines are expensive to develop and produce on a commercial scale, contributing to rising healthcare costs. Developability of Biotherapeutics: Computational Approaches describes applications of computational and molecular

Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics

Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics

Author: Yi Pan

Publisher: John Wiley & Sons

Published: 2013-10-07

Total Pages: 534

ISBN-13: 1118567811

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Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics An in-depth look at the latest research, methods, and applications in the field of protein bioinformatics This book presents the latest developments in protein bioinformatics, introducing for the first time cutting-edge research results alongside novel algorithmic and AI methods for the analysis of protein data. In one complete, self-contained volume, Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics addresses key challenges facing both computer scientists and biologists, arming readers with tools and techniques for analyzing and interpreting protein data and solving a variety of biological problems. Featuring a collection of authoritative articles by leaders in the field, this work focuses on the analysis of protein sequences, structures, and interaction networks using both traditional algorithms and AI methods. It also examines, in great detail, data preparation, simulation, experiments, evaluation methods, and applications. Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics: Highlights protein analysis applications such as protein-related drug activity comparison Incorporates salient case studies illustrating how to apply the methods outlined in the book Tackles the complex relationship between proteins from a systems biology point of view Relates the topic to other emerging technologies such as data mining and visualization Includes many tables and illustrations demonstrating concepts and performance figures Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics is an essential reference for bioinformatics specialists in research and industry, and for anyone wishing to better understand the rich field of protein bioinformatics.


Book Synopsis Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics by : Yi Pan

Download or read book Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics written by Yi Pan and published by John Wiley & Sons. This book was released on 2013-10-07 with total page 534 pages. Available in PDF, EPUB and Kindle. Book excerpt: Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics An in-depth look at the latest research, methods, and applications in the field of protein bioinformatics This book presents the latest developments in protein bioinformatics, introducing for the first time cutting-edge research results alongside novel algorithmic and AI methods for the analysis of protein data. In one complete, self-contained volume, Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics addresses key challenges facing both computer scientists and biologists, arming readers with tools and techniques for analyzing and interpreting protein data and solving a variety of biological problems. Featuring a collection of authoritative articles by leaders in the field, this work focuses on the analysis of protein sequences, structures, and interaction networks using both traditional algorithms and AI methods. It also examines, in great detail, data preparation, simulation, experiments, evaluation methods, and applications. Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics: Highlights protein analysis applications such as protein-related drug activity comparison Incorporates salient case studies illustrating how to apply the methods outlined in the book Tackles the complex relationship between proteins from a systems biology point of view Relates the topic to other emerging technologies such as data mining and visualization Includes many tables and illustrations demonstrating concepts and performance figures Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics is an essential reference for bioinformatics specialists in research and industry, and for anyone wishing to better understand the rich field of protein bioinformatics.

Concepts and Techniques in Genomics and Proteomics

Concepts and Techniques in Genomics and Proteomics

Author: N Saraswathy

Publisher: Elsevier

Published: 2011-07-01

Total Pages: 271

ISBN-13: 1908818050

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Concepts and techniques in genomics and proteomics covers the important concepts of high-throughput modern techniques used in the genomics and proteomics field. Each technique is explained with its underlying concepts, and simple line diagrams and flow charts are included to aid understanding and memory. A summary of key points precedes each chapter within the book, followed by detailed description in the subsections. Each subsection concludes with suggested relevant original references. Provides definitions for key concepts Case studies are included to illustrate ideas Important points to remember are noted


Book Synopsis Concepts and Techniques in Genomics and Proteomics by : N Saraswathy

Download or read book Concepts and Techniques in Genomics and Proteomics written by N Saraswathy and published by Elsevier. This book was released on 2011-07-01 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: Concepts and techniques in genomics and proteomics covers the important concepts of high-throughput modern techniques used in the genomics and proteomics field. Each technique is explained with its underlying concepts, and simple line diagrams and flow charts are included to aid understanding and memory. A summary of key points precedes each chapter within the book, followed by detailed description in the subsections. Each subsection concludes with suggested relevant original references. Provides definitions for key concepts Case studies are included to illustrate ideas Important points to remember are noted

Computational Resources for Understanding Biomacromolecular Covalent Modifications

Computational Resources for Understanding Biomacromolecular Covalent Modifications

Author: Dong Xu

Publisher: Frontiers Media SA

Published: 2021-09-14

Total Pages: 110

ISBN-13: 2889713199

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Book Synopsis Computational Resources for Understanding Biomacromolecular Covalent Modifications by : Dong Xu

Download or read book Computational Resources for Understanding Biomacromolecular Covalent Modifications written by Dong Xu and published by Frontiers Media SA. This book was released on 2021-09-14 with total page 110 pages. Available in PDF, EPUB and Kindle. Book excerpt:

The Proteomics Protocols Handbook

The Proteomics Protocols Handbook

Author: John M. Walker

Publisher: Springer Science & Business Media

Published: 2007-10-09

Total Pages: 969

ISBN-13: 1592598900

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Hands-on researchers describe in step-by-step detail 73 proven laboratory methods and bioinformatics tools essential for analysis of the proteome. These cutting-edge techniques address such important tasks as sample preparation, 2D-PAGE, gel staining, mass spectrometry, and post-translational modification. There are also readily reproducible methods for protein expression profiling, identifying protein-protein interactions, and protein chip technology, as well as a range of newly developed methodologies for determining the structure and function of a protein. The bioinformatics tools include those for analyzing 2D-GEL patterns, protein modeling, and protein identification. All laboratory-based protocols follow the successful Methods in Molecular BiologyTM series format, each offering step-by-step laboratory instructions, an introduction outlining the principle behind the technique, lists of the necessary equipment and reagents, and tips on troubleshooting and avoiding known pitfalls.


Book Synopsis The Proteomics Protocols Handbook by : John M. Walker

Download or read book The Proteomics Protocols Handbook written by John M. Walker and published by Springer Science & Business Media. This book was released on 2007-10-09 with total page 969 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hands-on researchers describe in step-by-step detail 73 proven laboratory methods and bioinformatics tools essential for analysis of the proteome. These cutting-edge techniques address such important tasks as sample preparation, 2D-PAGE, gel staining, mass spectrometry, and post-translational modification. There are also readily reproducible methods for protein expression profiling, identifying protein-protein interactions, and protein chip technology, as well as a range of newly developed methodologies for determining the structure and function of a protein. The bioinformatics tools include those for analyzing 2D-GEL patterns, protein modeling, and protein identification. All laboratory-based protocols follow the successful Methods in Molecular BiologyTM series format, each offering step-by-step laboratory instructions, an introduction outlining the principle behind the technique, lists of the necessary equipment and reagents, and tips on troubleshooting and avoiding known pitfalls.

An Introduction to Computational Biochemistry

An Introduction to Computational Biochemistry

Author: C. Stan Tsai

Publisher: John Wiley & Sons

Published: 2003-03-31

Total Pages: 381

ISBN-13: 0471461091

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This comprehensive text offers a solid introduction to the biochemical principles and skills required for any researcher applying computational tools to practical problems in biochemistry. Each chapter includes an introduction to the topic, a review of the biological concepts involved, a discussion of the programming and applications used, key references, and problem sets and answers. Providing detailed coverage of biochemical structures, enzyme reactions, metabolic simulation, genomic and proteomic analyses, and molecular modeling, this is the perfect resource for students and researchers in biochemistry, bioinformatics, bioengineering and computational science.


Book Synopsis An Introduction to Computational Biochemistry by : C. Stan Tsai

Download or read book An Introduction to Computational Biochemistry written by C. Stan Tsai and published by John Wiley & Sons. This book was released on 2003-03-31 with total page 381 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive text offers a solid introduction to the biochemical principles and skills required for any researcher applying computational tools to practical problems in biochemistry. Each chapter includes an introduction to the topic, a review of the biological concepts involved, a discussion of the programming and applications used, key references, and problem sets and answers. Providing detailed coverage of biochemical structures, enzyme reactions, metabolic simulation, genomic and proteomic analyses, and molecular modeling, this is the perfect resource for students and researchers in biochemistry, bioinformatics, bioengineering and computational science.

An Introduction to Statistical Learning

An Introduction to Statistical Learning

Author: Gareth James

Publisher: Springer Nature

Published: 2023-08-01

Total Pages: 617

ISBN-13: 3031387473

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An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R (ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users.


Book Synopsis An Introduction to Statistical Learning by : Gareth James

Download or read book An Introduction to Statistical Learning written by Gareth James and published by Springer Nature. This book was released on 2023-08-01 with total page 617 pages. Available in PDF, EPUB and Kindle. Book excerpt: An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R (ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users.

Nitric Oxide in Plants

Nitric Oxide in Plants

Author: Juan B. Barroso

Publisher: Frontiers Media SA

Published: 2021-08-26

Total Pages: 163

ISBN-13: 2889712354

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Book Synopsis Nitric Oxide in Plants by : Juan B. Barroso

Download or read book Nitric Oxide in Plants written by Juan B. Barroso and published by Frontiers Media SA. This book was released on 2021-08-26 with total page 163 pages. Available in PDF, EPUB and Kindle. Book excerpt: