ArticleDatabase : the journal of biological databases and curation2017
BELMiner: adapting a rule-based relation extraction system to extract biological expression language statements from bio-medical literature evidence sentences.
Article in Database : the journal of biological databases and curation, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- KGG: a fully automated workflow for creating disease-specific knowledge graphs.Bioinformatics (Oxford, England) · 2025Article
- A reproducible experimental survey on biomedical sentence similarity: A string-based method sets the state of the art.PloS one · 2022Article
- Deep semi-supervised learning ensemble framework for classifying co-mentions of human proteins and phenotypes.BMC bioinformatics · 2021Article
- Mining a stroke knowledge graph from literature.BMC bioinformatics · 2021Article
- Extraction of causal relations based on SBEL and BERT model.Database : the journal of biological databases and curation · 2021Article
- Data Integration Challenges for Machine Learning in Precision Medicine.Frontiers in medicine · 2021Review
- Article
- Deep learning with sentence embeddings pre-trained on biomedical corpora improves the performance of finding similar sentences in electronic medical records.BMC medical informatics and decision making · 2020Article
- Constructing knowledge graphs and their biomedical applications.Computational and structural biotechnology journal · 2020Review
- Using a Large Margin Context-Aware Convolutional Neural Network to Automatically Extract Disease-Disease Association from Literature: Comparative Analytic Study.JMIR medical informatics · 2019Article
- Hierarchical sequence labeling for extracting BEL statements from biomedical literature.BMC medical informatics and decision making · 2019Article
- Navigating the disease landscape: knowledge representations for contextualizing molecular signatures.Briefings in bioinformatics · 2019Review
- Combining relation extraction with function detection for BEL statement extraction.Database : the journal of biological databases and curation · 2019Article
- Relation extraction for biological pathway construction using node2vec.BMC bioinformatics · 2018Article
- BEL Commons: an environment for exploration and analysis of networks encoded in Biological Expression Language.Database : the journal of biological databases and curation · 2018Article
- Leveraging word embeddings and medical entity extraction for biomedical dataset retrieval using unstructured texts.Database : the journal of biological databases and curation · 2017Article
- BELTracker: evidence sentence retrieval for BEL statements.Database : the journal of biological databases and curation · 2016Article
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3 authors.
Funding
Abstract
Extracting meaningful relationships with semantic significance from biomedical literature is often a challenging task. BioCreative V track4 challenge for the first time has organized a comprehensive shared task to test the robustness of the text-mining algorithms in extracting semantically meaningful assertions from the evidence statement in biomedical text. In this work, we tested the ability of a rule-based semantic parser to extract Biological Expression Language (BEL) statements from evidence sentences culled out of biomedical literature as part of BioCreative V Track4 challenge. The system achieved an overall best F-measure of 21.29% in extracting the complete BEL statement. For relation extraction, the system achieved an F-measure of 65.13% on test data set. Our system achieved the best performance in five of the six criteria that was adopted for evaluation by the task organizers. Lack of ability to derive semantic inferences, limitation in the rule sets to map the textual extractions to BEL function were some of the reasons for low performance in extracting the complete BEL statement. Post shared task we also evaluated the impact of differential NER components on the ability to extract BEL statements on the test data sets besides making a single change in the rule sets that translate relation extractions into a BEL statement. There is a marked improvement by over 20% in the overall performance of the BELMiner's capability to extract BEL statement on the test set. The system is available as a REST-API at http://54.146.11.205:8484/BELXtractor/finder/. Database URL: http://54.146.11.205:8484/BELXtractor/finder/.
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