Fr. 179.00

Protein Function Prediction - Methods and Protocols

English · Paperback / Softback

Shipping usually within 6 to 7 weeks

Description

Read more

This volume presents established bioinformatics tools and databases for function prediction of proteins. Reflecting the diversity of this active field in bioinformatics, the chapters in this book discuss a variety of tools and resources such as sequence-, structure-, systems-, and interaction-based function prediction methods, tools for functional analysis of metagenomics data, detecting moonlighting-proteins, sub-cellular localization prediction, and pathway and comparative genomics databases. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, step-by-step instructions of how to use software and web resources, use cases, and tips on troubleshooting and avoiding known pitfalls.

Thorough and cutting-edge, Protein Function Prediction: Methods and Protocols is a valuable and practical guide for using bioinformatics tools for investigating protein function

List of contents

Using PFP and ESG Protein Function Prediction Web Servers.- GHOSTX: A Fast Sequence Homology Search Tool for Functional Annotation of Metagenomic Data.- From Gene Annotation to Function Prediction for Metagenomics.- An Agile Functional Analysis of Metagenomic Data using SUPER-FOCUS.- MPFit: Computational Tool for Predicting Moonlighting Proteins.- Predicting Secretory Proteins with SignalP.- The ProFunc Function Prediction Server.- G-LoSA for Prediction of Protein-Ligand Binding Sites and Structures.- Local Alignment of Ligand Binding Sites in Proteins for Polypharmacology and Drug Repositioning.- WATsite2.0 with PyMOL Plugin: Hydration Site Prediction and Visualization.- Enzyme Annotation and Metabolic Reconstruction Using KEGG.- Ortholog Identification and Comparative Analysis of Microbial Genomes using MBGD and RECOG.- Exploring Protein Function Using the Saccharomyces Genome Database.- Network-Based Gene Function Prediction in Mouse and Other Model Vertebrates using MouseNet Server.- The FANTOM5 Computation Ecosystem: Genomic Information Hub for Promoters and Active Enhancers.- Multi-Algorithm Particle Simulations with Spatiocyte.

Summary

This volume presents established bioinformatics tools and databases for function prediction of proteins. Reflecting the diversity of this active field in bioinformatics, the chapters in this book discuss a variety of tools and resources such as sequence-, structure-, systems-, and interaction-based function prediction methods, tools for functional analysis of metagenomics data, detecting moonlighting-proteins, sub-cellular localization prediction, and pathway and comparative genomics databases. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, step-by-step instructions of how to use software and web resources, use cases, and tips on troubleshooting and avoiding known pitfalls.

Thorough and cutting-edge, Protein Function Prediction: Methods and Protocols is a valuable and practical guide for using bioinformatics tools for investigating protein function

Product details

Assisted by Daisuk Kihara (Editor), Daisuke Kihara (Editor)
Publisher Springer, Berlin
 
Languages English
Product format Paperback / Softback
Released 31.05.2019
 
EAN 9781493983681
ISBN 978-1-4939-8368-1
No. of pages 239
Dimensions 178 mm x 13 mm x 254 mm
Weight 485 g
Illustrations X, 239 p. 82 illus., 71 illus. in color.
Series Methods in Molecular Biology
Methods in Molecular Biology
Subjects Natural sciences, medicine, IT, technology > Biology > Biochemistry, biophysics

B, Life Sciences, proteins, Biomedical and Life Sciences, Protein Science

Customer reviews

No reviews have been written for this item yet. Write the first review and be helpful to other users when they decide on a purchase.

Write a review

Thumbs up or thumbs down? Write your own review.

For messages to CeDe.ch please use the contact form.

The input fields marked * are obligatory

By submitting this form you agree to our data privacy statement.