Automatic extraction of keywords from scientific text: application to the knowledge domain of protein families

Publication type:
Journal article
Metadata:
Autoren
  • MA Andrade
  • A Valencia
Autoren-URL
https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=fis-test-1&SrcAuth=WosAPI&KeyUT=WOS:000076226300007&DestLinkType=FullRecord&DestApp=WOS_CPL
DOI
10.1093/bioinformatics/14.7.600
Externe Identifier
  • Clarivate Analytics Document Solution ID: 125FG
  • PubMed Identifier: 9730925
ISSN
1367-4803
Ausgabe der Veröffentlichung
7
Zeitschrift
BIOINFORMATICS
Paginierung
600 - 607
Datum der Veröffentlichung
1998
Status
Published
Titel
Automatic extraction of keywords from scientific text: application to the knowledge domain of protein families
Sub types
  • Article
Ausgabe der Zeitschrift
14

Data source: Web of Science (Lite)

Other metadata sources:
Abstract
<jats:title>Abstract</jats:title> <jats:p>MOTIVATION: Annotation of the biological function of different protein sequences is a time-consuming process currently performed by human experts. Genome analysis tools encounter great difficulty in performing this task. Database curators, developers of genome analysis tools and biologists in general could benefit from access to tools able to suggest functional annotations and facilitate access to functional information. APPROACH: We present here the first prototype of a system for the automatic annotation of protein function. The system is triggered by collections of s related to a given protein, and it is able to extract biological information directly from scientific literature, i.e. MEDLINE abstracts. Relevant keywords are selected by their relative accumulation in comparison with a domain-specific background distribution. Simultaneously, the most representative sentences and MEDLINE abstracts are selected and presented to the end-user. Evolutionary information is considered as a predominant characteristic in the domain of protein function. Our system consequently extracts domain-specific information from the analysis of a set of protein families. RESULTS: The system has been tested with different protein families, of which three examples are discussed in detail here: 'ataxia-telangiectasia associated protein', 'ran GTPase' and 'carbonic anhydrase'. We found generally good correlation between the amount of information provided to the system and the quality of the annotations. Finally, the current limitations and future developments of the system are discussed. AVAILABILITY: The current system can be considered as a prototype system. As such, it can be accessed as a server at http://columba.ebi.ac. uk:8765/andrade/abx. The system accepts text related to the protein or proteins to be evaluated (optimally, the result of a MEDLINE search by keyword) and the results are returned in the form of Web pages for keywords, sentences and s. SUPPLEMENTARY INFORMATION: Web pages containing full information on the examples mentioned in the text are available at: http://www.cnb.uam.es/ approximately cnbprot/keywords/ CONTACT: valencia@cnb.uam.es</jats:p>
Autoren
  • MA Andrade
  • A Valencia
DOI
10.1093/bioinformatics/14.7.600
eISSN
1367-4811
ISSN
1367-4803
Ausgabe der Veröffentlichung
7
Zeitschrift
Bioinformatics
Sprache
en
Online publication date
1998
Paginierung
600 - 607
Datum der Veröffentlichung
1998
Status
Published
Herausgeber
Oxford University Press (OUP)
Herausgeber URL
http://dx.doi.org/10.1093/bioinformatics/14.7.600
Datum der Datenerfassung
2023
Titel
Automatic extraction of keywords from scientific text: application to the knowledge domain of protein families.
Ausgabe der Zeitschrift
14

Data source: Crossref

Abstract
<h4>Motivation</h4>Annotation of the biological function of different protein sequences is a time-consuming process currently performed by human experts. Genome analysis tools encounter great difficulty in performing this task. Database curators, developers of genome analysis tools and biologists in general could benefit from access to tools able to suggest functional annotations and facilitate access to functional information.<h4>Approach</h4>We present here the first prototype of a system for the automatic annotation of protein function. The system is triggered by collections of s related to a given protein, and it is able to extract biological information directly from scientific literature, i.e. MEDLINE abstracts. Relevant keywords are selected by their relative accumulation in comparison with a domain-specific background distribution. Simultaneously, the most representative sentences and MEDLINE abstracts are selected and presented to the end-user. Evolutionary information is considered as a predominant characteristic in the domain of protein function. Our system consequently extracts domain-specific information from the analysis of a set of protein families.<h4>Results</h4>The system has been tested with different protein families, of which three examples are discussed in detail here: 'ataxia-telangiectasia associated protein', 'ran GTPase' and 'carbonic anhydrase'. We found generally good correlation between the amount of information provided to the system and the quality of the annotations. Finally, the current limitations and future developments of the system are discussed.<h4>Availability</h4>The current system can be considered as a prototype system. As such, it can be accessed as a server at http://columba.ebi.ac. uk:8765/andrade/abx. The system accepts text related to the protein or proteins to be evaluated (optimally, the result of a MEDLINE search by keyword) and the results are returned in the form of Web pages for keywords, sentences and s.<h4>Supplementary information</h4>Web pages containing full information on the examples mentioned in the text are available at: http://www.cnb.uam.es/ approximately cnbprot/keywords/<h4>Contact</h4>valencia@cnb.uam.es
Addresses
  • Protein Design Group, CNB-CSIC, Cantoblanco, E-28049 Madrid, Spain.
Autoren
  • MA Andrade
  • A Valencia
DOI
10.1093/bioinformatics/14.7.600
eISSN
1367-4811
Externe Identifier
  • PubMed Identifier: 9730925
Open access
false
ISSN
1367-4803
Ausgabe der Veröffentlichung
7
Zeitschrift
Bioinformatics (Oxford, England)
Schlüsselwörter
  • Proteins
  • Algorithms
  • Mathematical Computing
  • Forecasting
  • Automation
  • Internet
  • Abstracting and Indexing
  • MEDLINE
Sprache
eng
Medium
Print
Paginierung
600 - 607
Datum der Veröffentlichung
1998
Status
Published
Datum der Datenerfassung
1998
Titel
Automatic extraction of keywords from scientific text: application to the knowledge domain of protein families.
Sub types
  • Research Support, Non-U.S. Gov't
  • Journal Article
Ausgabe der Zeitschrift
14

Data source: Europe PubMed Central

Abstract
MOTIVATION: Annotation of the biological function of different protein sequences is a time-consuming process currently performed by human experts. Genome analysis tools encounter great difficulty in performing this task. Database curators, developers of genome analysis tools and biologists in general could benefit from access to tools able to suggest functional annotations and facilitate access to functional information. APPROACH: We present here the first prototype of a system for the automatic annotation of protein function. The system is triggered by collections of s related to a given protein, and it is able to extract biological information directly from scientific literature, i.e. MEDLINE abstracts. Relevant keywords are selected by their relative accumulation in comparison with a domain-specific background distribution. Simultaneously, the most representative sentences and MEDLINE abstracts are selected and presented to the end-user. Evolutionary information is considered as a predominant characteristic in the domain of protein function. Our system consequently extracts domain-specific information from the analysis of a set of protein families. RESULTS: The system has been tested with different protein families, of which three examples are discussed in detail here: 'ataxia-telangiectasia associated protein', 'ran GTPase' and 'carbonic anhydrase'. We found generally good correlation between the amount of information provided to the system and the quality of the annotations. Finally, the current limitations and future developments of the system are discussed. AVAILABILITY: The current system can be considered as a prototype system. As such, it can be accessed as a server at http://columba.ebi.ac. uk:8765/andrade/abx. The system accepts text related to the protein or proteins to be evaluated (optimally, the result of a MEDLINE search by keyword) and the results are returned in the form of Web pages for keywords, sentences and s. SUPPLEMENTARY INFORMATION: Web pages containing full information on the examples mentioned in the text are available at: http://www.cnb.uam.es/ approximately cnbprot/keywords/ CONTACT: valencia@cnb.uam.es
Autoren
  • MA Andrade
  • A Valencia
Autoren-URL
https://www.ncbi.nlm.nih.gov/pubmed/9730925
DOI
10.1093/bioinformatics/14.7.600
ISSN
1367-4803
Ausgabe der Veröffentlichung
7
Zeitschrift
Bioinformatics
Schlüsselwörter
  • Abstracting and Indexing
  • Algorithms
  • Automation
  • Forecasting
  • Internet
  • MEDLINE
  • Mathematical Computing
  • Proteins
Sprache
eng
Country
England
Paginierung
600 - 607
PII
btb089
Datum der Veröffentlichung
1998
Status
Published
Datum, an dem der Datensatz öffentlich gemacht wurde
1998
Titel
Automatic extraction of keywords from scientific text: application to the knowledge domain of protein families.
Sub types
  • Journal Article
  • Research Support, Non-U.S. Gov't
Ausgabe der Zeitschrift
14

Data source: PubMed

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