PESCADOR, a web-based tool to assist text-mining of biointeractions extracted from PubMed queries

Publication type:
Journal article
Metadata:
Autoren
  • Adriano Barbosa-Silva
  • Jean-Fred Fontaine
  • Elisa R Donnard
  • Fernanda Stussi
  • J Miguel Ortega
  • Miguel A Andrade-Navarro
Autoren-URL
https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=fis-test-1&SrcAuth=WosAPI&KeyUT=WOS:000297642700001&DestLinkType=FullRecord&DestApp=WOS_CPL
DOI
10.1186/1471-2105-12-435
Externe Identifier
  • Clarivate Analytics Document Solution ID: 856LN
  • PubMed Identifier: 22070195
ISSN
1471-2105
Zeitschrift
BMC BIOINFORMATICS
Artikelnummer
ARTN 435
Datum der Veröffentlichung
2011
Status
Published
Titel
PESCADOR, a web-based tool to assist text-mining of biointeractions extracted from PubMed queries
Sub types
  • Article
Ausgabe der Zeitschrift
12

Data source: Web of Science (Lite)

Other metadata sources:
Autoren
  • Adriano Barbosa-Silva
  • Jean-Fred Fontaine
  • Elisa R Donnard
  • Fernanda Stussi
  • J Miguel Ortega
  • Miguel A Andrade-Navarro
DOI
10.1186/1471-2105-12-435
eISSN
1471-2105
Ausgabe der Veröffentlichung
1
Zeitschrift
BMC Bioinformatics
Sprache
en
Artikelnummer
435
Online publication date
2011
Datum der Veröffentlichung
2011
Status
Published
Herausgeber
Springer Science and Business Media LLC
Herausgeber URL
http://dx.doi.org/10.1186/1471-2105-12-435
Datum der Datenerfassung
2019
Titel
PESCADOR, a web-based tool to assist text-mining of biointeractions extracted from PubMed queries
Ausgabe der Zeitschrift
12

Data source: Crossref

Abstract
<h4>Background</h4>Biological function is greatly dependent on the interactions of proteins with other proteins and genes. Abstracts from the biomedical literature stored in the NCBI's PubMed database can be used for the derivation of interactions between genes and proteins by identifying the co-occurrences of their terms. Often, the amount of interactions obtained through such an approach is large and may mix processes occurring in different contexts. Current tools do not allow studying these data with a focus on concepts of relevance to a user, for example, interactions related to a disease or to a biological mechanism such as protein aggregation.<h4>Results</h4>To help the concept-oriented exploration of such data we developed PESCADOR, a web tool that extracts a network of interactions from a set of PubMed abstracts given by a user, and allows filtering the interaction network according to user-defined concepts. We illustrate its use in exploring protein aggregation in neurodegenerative disease and in the expansion of pathways associated to colon cancer.<h4>Conclusions</h4>PESCADOR is a platform independent web resource available at: http://cbdm.mdc-berlin.de/tools/pescador/
Addresses
  • Computational Biology and Data Mining Group, Max Delbrück Center for Molecular Medicine, Robert-Rössle-Strasse, 10, D-13125, Berlin, Germany. adriano.barbosa@mdc-berlin.de
Autoren
  • Adriano Barbosa-Silva
  • Jean-Fred Fontaine
  • Elisa R Donnard
  • Fernanda Stussi
  • J Miguel Ortega
  • Miguel A Andrade-Navarro
DOI
10.1186/1471-2105-12-435
eISSN
1471-2105
Externe Identifier
  • PubMed Identifier: 22070195
  • PubMed Central ID: PMC3228910
Open access
true
ISSN
1471-2105
Zeitschrift
BMC bioinformatics
Schlüsselwörter
  • Humans
  • Colorectal Neoplasms
  • Neurodegenerative Diseases
  • Proteins
  • Internet
  • Software
  • PubMed
  • Data Mining
Sprache
eng
Medium
Electronic
Online publication date
2011
Open access status
Open Access
Paginierung
435
Datum der Veröffentlichung
2011
Status
Published
Publisher licence
CC BY
Datum der Datenerfassung
2011
Titel
PESCADOR, a web-based tool to assist text-mining of biointeractions extracted from PubMed queries.
Sub types
  • Research Support, Non-U.S. Gov't
  • data-paper
  • Journal Article
Ausgabe der Zeitschrift
12

Files

https://bmcbioinformatics.biomedcentral.com/counter/pdf/10.1186/1471-2105-12-435 https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22070195/pdf/?tool=EBI https://europepmc.org/articles/PMC3228910?pdf=render

Data source: Europe PubMed Central

Abstract
BACKGROUND: Biological function is greatly dependent on the interactions of proteins with other proteins and genes. Abstracts from the biomedical literature stored in the NCBI's PubMed database can be used for the derivation of interactions between genes and proteins by identifying the co-occurrences of their terms. Often, the amount of interactions obtained through such an approach is large and may mix processes occurring in different contexts. Current tools do not allow studying these data with a focus on concepts of relevance to a user, for example, interactions related to a disease or to a biological mechanism such as protein aggregation. RESULTS: To help the concept-oriented exploration of such data we developed PESCADOR, a web tool that extracts a network of interactions from a set of PubMed abstracts given by a user, and allows filtering the interaction network according to user-defined concepts. We illustrate its use in exploring protein aggregation in neurodegenerative disease and in the expansion of pathways associated to colon cancer. CONCLUSIONS: PESCADOR is a platform independent web resource available at: http://cbdm.mdc-berlin.de/tools/pescador/
Date of acceptance
2011
Autoren
  • Adriano Barbosa-Silva
  • Jean-Fred Fontaine
  • Elisa R Donnard
  • Fernanda Stussi
  • J Miguel Ortega
  • Miguel A Andrade-Navarro
Autoren-URL
https://www.ncbi.nlm.nih.gov/pubmed/22070195
DOI
10.1186/1471-2105-12-435
eISSN
1471-2105
Externe Identifier
  • PubMed Central ID: PMC3228910
Zeitschrift
BMC Bioinformatics
Schlüsselwörter
  • Colorectal Neoplasms
  • Data Mining
  • Humans
  • Internet
  • Neurodegenerative Diseases
  • Proteins
  • PubMed
  • Software
Sprache
eng
Country
England
Paginierung
435
PII
1471-2105-12-435
Datum der Veröffentlichung
2011
Status
Published online
Datum, an dem der Datensatz öffentlich gemacht wurde
2012
Titel
PESCADOR, a web-based tool to assist text-mining of biointeractions extracted from PubMed queries.
Sub types
  • Journal Article
  • Research Support, Non-U.S. Gov't
Ausgabe der Zeitschrift
12

Data source: PubMed

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