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Protein Bioinformatics

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Cover of 'Protein Bioinformatics'

Table of Contents

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    Book Overview
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    Chapter 1 Protein Bioinformatics Databases and Resources
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    Chapter 2 UniProt Protein Knowledgebase
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    Chapter 3 Tutorial on Protein Ontology Resources
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    Chapter 4 CATH-Gene3D: Generation of the Resource and Its Use in Obtaining Structural and Functional Annotations for Protein Sequences
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    Chapter 5 Structure-Based Virtual Screening
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    Chapter 6 Bioinformatics Analysis of Protein Phosphorylation in Plant Systems Biology Using P3DB
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    Chapter 7 Navigating the Glycome Space and Connecting the Glycoproteome
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    Chapter 8 Impact of Nonsynonymous Single-Nucleotide Variations on Post-Translational Modification Sites in Human Proteins
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    Chapter 9 Analysis of Cysteine Redox Post-Translational Modifications in Cell Biology and Drug Pharmacology
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    Chapter 10 Analysis of Protein Phosphorylation and Its Functional Impact on Protein–Protein Interactions via Text Mining of the Scientific Literature
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    Chapter 11 Functional Interaction Network Construction and Analysis for Disease Discovery
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    Chapter 12 Prediction of Protein Interactions by Structural Matching: Prediction of PPI Networks and the Effects of Mutations on PPIs that Combines Sequence and Structural Information
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    Chapter 13 NDEx: A Community Resource for Sharing and Publishing of Biological Networks
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    Chapter 14 Bioinformatics Analysis of Functional Associations of PTMs
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    Chapter 15 Bioinformatics Analysis of PTM-Modified Protein Interaction Networks and Complexes
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    Chapter 16 iPTMnet: Integrative Bioinformatics for Studying PTM Networks
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    Chapter 17 Protein Identification from Tandem Mass Spectra by Database Searching
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    Chapter 18 Bioinformatics Analysis of Top-Down Mass Spectrometry Data with ProSight Lite
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    Chapter 19 Mapping Biological Networks from Quantitative Data-Independent Acquisition Mass Spectrometry: Data to Knowledge Pipelines
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    Chapter 20 Annotation of Alternatively Spliced Proteins and Transcripts with Protein-Folding Algorithms and Isoform-Level Functional Networks
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    Chapter 21 Computational and Statistical Methods for High-Throughput Mass Spectrometry-Based PTM Analysis
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    Chapter 22 Cross-Species PTM Mapping from Phosphoproteomic Data
Attention for Chapter 22: Cross-Species PTM Mapping from Phosphoproteomic Data
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Chapter title
Cross-Species PTM Mapping from Phosphoproteomic Data
Chapter number 22
Book title
Protein Bioinformatics
Published in
Methods in molecular biology, February 2017
DOI 10.1007/978-1-4939-6783-4_22
Pubmed ID
Book ISBNs
978-1-4939-6781-0, 978-1-4939-6783-4
Authors

Rima Chaudhuri, Jean Yee Hwa Yang

Editors

Cathy H. Wu, Cecilia N. Arighi, Karen E. Ross

Abstract

Protein post-translational modifications (PTMs) are crucial for signal transduction in cells. In order to understand key cell signaling events, identification of functionally important PTMs, which are more likely to be evolutionarily conserved, is necessary. In recent times, high-throughput mass spectrometry (MS) has made quantitative datasets in diverse species readily available, which has led to a growing need for tools to facilitate cross-species comparison of PTM data. Cross-species comparison of PTM sites is difficult since they often lie in structurally disordered protein domains. Current tools that address this can only map known PTMs between species based on previously annotated orthologous phosphosites and do not enable cross-species mapping of newly identified modification sites. Here, we describe an automated web-based tool, PhosphOrtholog, that accurately maps annotated and novel orthologous PTM sites from high-throughput MS-based experimental data obtained from different species without relying on existing PTM databases. Identification of conserved PTMs across species from large-scale experimental data increases our knowledgebase of evolutionarily conserved and functional PTM sites that influence most biological processes. In this Chapter, we illustrate with examples how to use PhosphOrtholog to map novel PTM sites from cross-species MS-based phosphoproteomics data.