Computational Methods for Predicting Post-Translational Modification Sites PDF Download
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Author: Dukka B. KC
Publisher: Springer Nature
ISBN: 1071623176
Category : Science
Languages : en
Pages : 337
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Book Description
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.
Author: Dukka B. KC
Publisher: Springer Nature
ISBN: 1071623176
Category : Science
Languages : en
Pages : 337
Get Book Here
Book Description
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.
Author: Yi Pan
Publisher: John Wiley & Sons
ISBN: 1118567811
Category : Medical
Languages : en
Pages : 534
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Book Description
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.
Author: Sandeep Kumar
Publisher: CRC Press
ISBN: 1482246155
Category : Medical
Languages : en
Pages : 312
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Book Description
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
Author: N Saraswathy
Publisher: Elsevier
ISBN: 1908818050
Category : Science
Languages : en
Pages : 271
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Book Description
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
Author: Dong Xu
Publisher: Frontiers Media SA
ISBN: 2889713199
Category : Science
Languages : en
Pages : 110
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Book Description
Author: C. Stan Tsai
Publisher: John Wiley & Sons
ISBN: 0471461091
Category : Science
Languages : en
Pages : 381
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Book Description
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.
Author: John M. Walker
Publisher: Springer Science & Business Media
ISBN: 1592598900
Category : Science
Languages : en
Pages : 969
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Book Description
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.
Author: Kavi Kishor P.B.
Publisher: Springer
ISBN: 8132218809
Category : Science
Languages : en
Pages : 296
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Book Description
A common approach to understanding the functional repertoire of a genome is through functional genomics. With systems biology burgeoning, bioinformatics has grown to a larger extent for plant genomes where several applications in the form of protein-protein interactions (PPI) are used to predict the function of proteins. With plant genes evolutionarily conserved, the science of bioinformatics in agriculture has caught interest with myriad of applications taken from bench side to in silico studies. A multitude of technologies in the form of gene analysis, biochemical pathways and molecular techniques have been exploited to an extent that they consume less time and have been cost-effective to use. As genomes are being sequenced, there is an increased amount of expression data being generated from time to time matching the need to link the expression profiles and phenotypic variation to the underlying genomic variation. This would allow us to identify candidate genes and understand the molecular basis/phenotypic variation of traits. While many bioinformatics methods like expression and whole genome sequence data of organisms in biological databases have been used in plants, we felt a common reference showcasing the reviews for such analysis is wanting. We envisage that this dearth would be facilitated in the form of this Springer book on Agricultural Bioinformatics. We thank all the authors and the publishers Springer, Germany for providing us an opportunity to review the bioinformatics works that the authors have carried in the recent past and hope the readers would find this book attention grabbing.
Author: Gareth James
Publisher: Springer Nature
ISBN: 3031387473
Category : Mathematics
Languages : en
Pages : 617
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Book Description
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.
Author: Thomas E. Creighton
Publisher: Macmillan
ISBN: 9780716770305
Category : Medical
Languages : en
Pages : 534
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Book Description
Organized on a combined basis of chronology and of structural and functional hierarchy, This comprehensive text describes all aspects of proteins--biosynthesis, evolution, dynamics, ligand binding, catalysis, and energy transduction--not just their structures. This edition (first was 1984) is thoroughly updated--especially in the area of protein biosynthesis--and features end-of-chapter exercises and problems, many of which require the student to consult the cited literature in order to obtain the answer. Annotation copyright by Book News, Inc., Portland, OR
