PPaxe: easy extraction of protein occurrence and interactions from the scientific literature
Abstract Motivation Protein–protein interactions (PPIs) are very important to build models for understanding many biological processes. Although several databases hold many of these interactions, exploring them, selecting those relevant for a given subject and contextualizing them can be a difficult...
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| Published in: | Bioinformatics Vol. 35; no. 14; pp. 2523 - 2524 |
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| Main Authors: | , |
| Format: | Journal Article |
| Language: | English |
| Published: |
England
Oxford University Press
15.07.2019
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| ISSN: | 1367-4803, 1367-4811, 1460-2059, 1367-4811 |
| Online Access: | Get full text |
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| Summary: | Abstract
Motivation
Protein–protein interactions (PPIs) are very important to build models for understanding many biological processes. Although several databases hold many of these interactions, exploring them, selecting those relevant for a given subject and contextualizing them can be a difficult task for researchers. Extracting PPIs directly from the scientific literature can be very helpful for providing such context, as the sentences describing these interactions may give insights to researchers in helpful ways.
Results
We have developed PPaxe, a python module and a web application that allows users to extract PPIs and protein occurrence from a given set of PubMed and PubMedCentral articles. It presents the results of the analysis in different ways to help researchers export, filter and analyze the results easily.
Availability and implementation
PPaxe web demo is freely available at https://compgen.bio.ub.edu/PPaxe. All the software can be downloaded from https://compgen.bio.ub.edu/PPaxe/download, including a command-line version and docker containers for an easy installation.
Supplementary information
Supplementary data are available at Bioinformatics online. |
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| ISSN: | 1367-4803 1367-4811 1460-2059 1367-4811 |
| DOI: | 10.1093/bioinformatics/bty988 |