ArticleBioinformatics (Oxford, England)2010
Evaluation of linguistic features useful in extraction of interactions from PubMed; application to annotating known, high-throughput and predicted interactions in I2D.
Article in Bioinformatics (Oxford, England), 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
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Who cites it
34 citing papers in PubMed.
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- Deciphering key genes involved in cisplatin resistance in kidney renal clear cell carcinoma through a combinedOncology research · 2023Article
- Challenges and Limitations of Biological Network Analysis.Biotech (Basel (Switzerland)) · 2022Article
- Triage of documents containing protein interactions affected by mutations using an NLP based machine learning approach.BMC genomics · 2020Article
- Extracting chemical-protein interactions from literature using sentence structure analysis and feature engineering.Database : the journal of biological databases and curation · 2019Article
- PregOMICS-Leveraging systems biology and bioinformatics for drug repurposing in maternal-child health.American journal of reproductive immunology (New York, N.Y. : 1989) · 2018Article
- Opportunities and obstacles for deep learning in biology and medicine.Journal of the Royal Society, Interface · 2018Review
- Article
- RWCFusion: identifying phenotype-specific cancer driver gene fusions based on fusion pair random walk scoring method.Oncotarget · 2016Article
- Protein-protein interaction extraction with feature selection by evaluating contribution levels of groups consisting of related features.BMC bioinformatics · 2016Article
- APID interactomes: providing proteome-based interactomes with controlled quality for multiple species and derived networks.Nucleic acids research · 2016Article
- Did we learn something new on pemphigoid autoimmune blistering diseases?Clinical oral investigations · 2016Article
- Text Mining for Protein Docking.PLoS computational biology · 2015Article
- Extraction of Protein-Protein Interaction from Scientific Articles by Predicting Dominant Keywords.BioMed research international · 2015Article
- STRING v10: protein-protein interaction networks, integrated over the tree of life.Nucleic acids research · 2015Article
- Machine learning applications in cancer prognosis and prediction.Computational and structural biotechnology journal · 2015Review
- Dead enzymes in the aldehyde dehydrogenase gene family: role in drug metabolism and toxicology.Expert opinion on drug metabolism & toxicology · 2015Review
- Protein-protein interactions and genetic diseases: The interactome.Biochimica et biophysica acta · 2014Review
- The MIntAct project--IntAct as a common curation platform for 11 molecular interaction databases.Nucleic acids research · 2014Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
motivationIdentification and characterization of protein-protein interactions (PPIs) is one of the key aims in biological research. While previous research in text mining has made substantial progress in automatic PPI detection from literature, the need to improve the precision and recall of the process remains. More accurate PPI detection will also improve the ability to extract experimental data related to PPIs and provide multiple evidence for each interaction.
resultsWe developed an interaction detection method and explored the usefulness of various features in automatically identifying PPIs in text. The results show that our approach outperforms other systems using the AImed dataset. In the tests where our system achieves better precision with reduced recall, we discuss possible approaches for improvement. In addition to test datasets, we evaluated the performance on interactions from five human-curated databases-BIND, DIP, HPRD, IntAct and MINT-where our system consistently identified evidence for approximately 60% of interactions when both proteins appear in at least one sentence in the PubMed abstract. We then applied the system to extract articles from PubMed to annotate known, high-throughput and interologous interactions in I(2)D. AVAILABILITY: The data and software are available at: http://www.cs.utoronto.ca/ approximately juris/data/BI09/.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.