Cited by 89Biomedical Text Mining and OntologiesBioinformatics and Genomic NetworksGene Regulatory Network Analysis

Text Mining for Metabolic Pathways, Signaling Cascades, and Protein Networks

Hoffmann, Robert, Krallinger, Martin, Andres, Eduardo, Tamames, Javier, Blaschke, Christian, Valencia, Alfonso·2005·Science's STKE

Abstract

The complexity of the information stored in databases and publications on metabolic and signaling pathways, the high throughput of experimental data, and the growing number of publications make it imperative to provide systems to help the researcher navigate through these interrelated information resources. Text-mining methods have started to play a key role in the creation and maintenance of links between the information stored in biological databases and its original sources in the literature. These links will be extremely useful for database updating and curation, especially if a number of technical problems can be solved satisfactorily, including the identification of protein and gene names (entities in general) and the characterization of their types of interactions. The first generation of openly accessible text-mining systems, such as iHOP (Information Hyperlinked over Proteins), provides additional functions to facilitate the reconstruction of protein interaction networks, combine database and text information, and support the scientist in the formulation of novel hypotheses. The next challenge is the generation of comprehensive information regarding the general function of signaling pathways and protein interaction networks.

Integrity signals

Registry

Crossref · 10.1126/stke.2832005pe21

Cites

26 of 26 references verified0 citation errors · 0 not checkable

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  • Pathway data is estimated from text-mining projects to be present in at least 10% of the over 20 million articles currently indexed by PubMed.

    “Pathway data recorded in the literature (estimated from text-mining projects23 to be present in at least 10% of the over 20 million articles currently indexed by PubMed).”

    From The BioPAX community standard for pathway data sharing (2010) · cites this paper as [23]

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Authors
Hoffmann, R., Krallinger, M., Andres, E., Tamames, J., Blaschke, C., & Valencia, A.
Affiliations
  • Consejo Superior de Investigaciones Científicas (ES)
  • Protein Design Group, National Center for Biotechnology, CNB-CSIC, Darwin 3, Cantoblanco, 28049 Madrid, Spain.
  • BioAlmai, Tres Cantos, Madrid, Spain.
Venue
Science's STKE
Published
2005-05-10
Volume
2005
Issue
283
Pages
pe21-pe21
ISSN
1525-8882 (ISSN-L)
OpenAlex
W2126469373
Cited by
88
References
26
Citations by year
2025: 2 · 2023: 1 · 2018: 2 · 2017: 3 · 2015: 2 · 2014: 4 · 2013: 7 · 2012: 5
FWCI
4.49
Type
journal article
Language
en
Open access
closed
Locations
  • Science s STKE (publishedVersion)
  • PubMed (publishedVersion)
  • DIGITAL.CSIC (Spanish National Research Council (CSIC)) (acceptedVersion)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Biomedical Text Mining and Ontologies
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
Keywords
text mining, metabolic pathways, signaling pathways, protein-protein interaction network, entity recognition, IHOP
MeSH terms
Animals, Dictionaries as Topic, Enzymes, Genes, Humans, Metabolism, Terminology as Topic, Proteins, Signal Transduction, Databases, Factual, Information Storage and Retrieval, Information Management, Knowledge Bases

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