Mining literature for protein-protein interactions

By Edward M. Marcotte, Ioannis Xenarios, David S. Eisenberg. Bioinform., 2001

333 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/fd86575193f0dd1b79ab668a6998108403b5780c

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In Molecular Biology

Citations in the corpus

Textpresso: An Ontology-Based Information Retrieval and Extraction System for Biological Literature (2004, background): “Other machine learning approaches have classiﬁed abstracts and sentences for relevant interactions, but have not extracted information (Marcotte et al. 2001; Donaldson et al. 2003).”
PreBIND and Textomy – mining the biomedical literature for protein-protein interactions using a support vector machine (2003, methodology): “[13] recently used a related method (Bayesian) to classify articles that described protein-protein interaction information.”
DIP: The Database of Interacting Proteins: 2001 update (2001, positive): “We have used the abstracts of articles present in DIP to train a Bayesian classifier (6) to extract abstracts from MEDLINE that potentially describe protein interactions.”
Comparative experiments on learning information extractors for proteins and their interactions (2005, background): “Several projects have focused on extracting relations from biomedical text, such as identifying gene-disease relations, subcellular localizations, or protein interactions [15,46,18,25,3,41,48,51,34].”
Mining the Biomedical Literature in the Genomic Era: An Overview (2003, positive): “Marcotte et al. (2001) apply a Bayes classi(cid:142) er that relies on discriminating terms to identify abstracts that discuss protein–protein interactions.”
Mining knowledge from text using information extraction (2005, background): “Another approach we have taken to identifying protein interactions is based on co-citation [39].”
Extracting interactions between proteins from the literature (2008, neutral): “[85] was only interested in retrieving a large number of documents that probably contained information about protein–protein interactions.”
STRING: known and predicted protein–protein associations, integrated and transferred across organisms (2004, background): “Another important source of protein association information is the published literature (18,19).”
Implementing the iHOP concept for navigation of biomedical literature (2005, background): “…2003; Mika and Rost, 2004) and novel ideas for the analysis of large-scale experiments have also been introduced (Tanabe et al., 1999; Blaschke and Valencia, 2001; Friedman et al., 2001; Jenssen et al., 2001; Masys et al., 2001; Park et al., 2001; Raychaudhuri et al., 2002; Glenisson et al., 2004).”
DIP, the Database of Interacting Proteins: a research tool for studying cellular networks of protein interactions (2002, methodology): “These include automated searches of the MEDLINE database both against a strict set of keywords as well as searches based on the data-mining strategy (14).”
Accomplishments and challenges in literature data mining for biology (2002, background): “There are other papers (Andrade and Valencia, 1998; Blaschke et al. , 1999; Craven and Kumlien, 1999; Marcotte et al. , 2001, etc.) that we did not discuss and they would be worth further reading to gain a more comprehensive understanding of the ﬁeld.”