ArticlePloS one2013
Approximate subgraph matching-based literature mining for biomedical events and relations.
Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- Leveraging shortest dependency paths in low-resource biomedical relation extraction.BMC medical informatics and decision making · 2024Article
- A reproducible experimental survey on biomedical sentence similarity: A string-based method sets the state of the art.PloS one · 2022Article
- Article
- Identification of intestinal flora-related key genes and therapeutic drugs in colorectal cancer.BMC medical genomics · 2020Article
- Named Entity Recognition and Relation Detection for Biomedical Information Extraction.Frontiers in cell and developmental biology · 2020Review
- Immune-centric network of cytokines and cells in disease context identified by computational mining of PubMed.Nature biotechnology · 2018Article
- Natural language processing in text mining for structural modeling of protein complexes.BMC bioinformatics · 2018Article
- Exploiting graph kernels for high performance biomedical relation extraction.Journal of biomedical semantics · 2018Article
- BioCreative VI Precision Medicine Track system performance is constrained by entity recognition and variations in corpus characteristics.Database : the journal of biological databases and curation · 2018Article
- NegBio: a high-performance tool for negation and uncertainty detection in radiology reports.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2018Article
- Bridging semantics and syntax with graph algorithms-state-of-the-art of extracting biomedical relations.Briefings in bioinformatics · 2017Article
- Subgraph augmented non-negative tensor factorization (SANTF) for modeling clinical narrative text.Journal of the American Medical Informatics Association : JAMIA · 2015Article
- Extracting drug-drug interactions from literature using a rich feature-based linear kernel approach.Journal of biomedical informatics · 2015Article
- Extraction of relations between genes and diseases from text and large-scale data analysis: implications for translational research.BMC bioinformatics · 2015Article
- Optimizing graph-based patterns to extract biomedical events from the literature.BMC bioinformatics · 2015Article
- Article
- Overview of the Cancer Genetics and Pathway Curation tasks of BioNLP Shared Task 2013.BMC bioinformatics · 2015Article
- Discovering relations between indirectly connected biomedical concepts.Journal of biomedical semantics · 2015Article
- An Overview of Biomolecular Event Extraction from Scientific Documents.Computational and mathematical methods in medicine · 2015Review
- Natural language processing pipelines to annotate BioC collections with an application to the NCBI disease corpus.Database : the journal of biological databases and curation · 2014Article
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Authors and funding
4 authors.
Funding
Abstract
The biomedical text mining community has focused on developing techniques to automatically extract important relations between biological components and semantic events involving genes or proteins from literature. In this paper, we propose a novel approach for mining relations and events in the biomedical literature using approximate subgraph matching. Extraction of such knowledge is performed by searching for an approximate subgraph isomorphism between key contextual dependencies and input sentence graphs. Our approach significantly increases the chance of retrieving relations or events encoded within complex dependency contexts by introducing error tolerance into the graph matching process, while maintaining the extraction precision at a high level. When evaluated on practical tasks, it achieves a 51.12% F-score in extracting nine types of biological events on the GE task of the BioNLP-ST 2011 and an 84.22% F-score in detecting protein-residue associations. The performance is comparable to the reported systems across these tasks, and thus demonstrates the generalizability of our proposed approach.
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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.