ArticleDatabase : the journal of biological databases and curation2013
PPInterFinder--a mining tool for extracting causal relations on human proteins from literature.
Article in Database : the journal of biological databases and curation, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
23 citing papers in PubMed, 71 citations in OpenAlex.
- Reduction of supervision for biomedical knowledge discovery.BMC bioinformatics · 2025Article
- A comprehensive large scale biomedical knowledge graph for AI powered data driven biomedical research.bioRxiv : the preprint server for biology · 2025Article
- Large Language Models and Genomics for Summarizing the Role of microRNA in Regulating mRNA Expression.Biomedicines · 2024Article
- A Study of Biomedical Relation Extraction Using GPT Models.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2024Article
- Expanding a database-derived biomedical knowledge graph via multi-relation extraction from biomedical abstracts.BioData mining · 2022Article
- LPInsider: a webserver for lncRNA-protein interaction extraction from the literature.BMC bioinformatics · 2022Article
- Overview of methods for characterization and visualization of a protein-protein interaction network in a multi-omics integration context.Frontiers in molecular biosciences · 2022Review
- Text Mining and Machine Learning Protocol for Extracting Human-Related Protein Phosphorylation Information from PubMed.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Text mining for identification of biological entities related to antibiotic resistant organisms.PeerJ · 2022Article
- Interactome of SARS-CoV-2 / nCoV19 modulated host proteins with computationally predicted PPIs.Research square · 2020Article
- OmixLitMiner: A Bioinformatics Tool for Prioritizing Biological Leads from 'Omics Data Using Literature Retrieval and Data Mining.International journal of molecular sciences · 2020Article
- DES-ROD: Exploring Literature to Develop New Links between RNA Oxidation and Human Diseases.Oxidative medicine and cellular longevity · 2020Article
- Literature-Based Enrichment Insights into Redox Control of Vascular Biology.Oxidative medicine and cellular longevity · 2019Review
- Automatic extraction of protein-protein interactions using grammatical relationship graph.BMC medical informatics and decision making · 2018Article
- Natural language processing in text mining for structural modeling of protein complexes.BMC bioinformatics · 2018Article
- A Review of Recent Advancement in Integrating Omics Data with Literature Mining towards Biomedical Discoveries.International journal of genomics · 2017Review
- Distributed smoothed tree kernel for protein-protein interaction extraction from the biomedical literature.PloS one · 2017Article
- Large-scale extraction of gene interactions from full-text literature using DeepDive.Bioinformatics (Oxford, England) · 2016Article
- Towards Evidence-based Precision Medicine: Extracting Population Information from Biomedical Text using Binary Classifiers and Syntactic Patterns.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2016Article
- Text Mining for Protein Docking.PLoS computational biology · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
One of the most common and challenging problem in biomedical text mining is to mine protein-protein interactions (PPIs) from MEDLINE abstracts and full-text research articles because PPIs play a major role in understanding the various biological processes and the impact of proteins in diseases. We implemented, PPInterFinder--a web-based text mining tool to extract human PPIs from biomedical literature. PPInterFinder uses relation keyword co-occurrences with protein names to extract information on PPIs from MEDLINE abstracts and consists of three phases. First, it identifies the relation keyword using a parser with Tregex and a relation keyword dictionary. Next, it automatically identifies the candidate PPI pairs with a set of rules related to PPI recognition. Finally, it extracts the relations by matching the sentence with a set of 11 specific patterns based on the syntactic nature of PPI pair. We find that PPInterFinder is capable of predicting PPIs with the accuracy of 66.05% on AIMED corpus and outperforms most of the existing systems. DATABASE URL: http://www.biomining-bu.in/ppinterfinder/
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Registered trials
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.