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Updated: Jan 8, 2026

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
Published on: February 23, 2019
S2CIE: semantic, syntactic, and context-based information extraction for AOP development
Saurav Kumar1, Shubh Sharma2, Deepika Deepika1
1IISPV, Departament d' Enginyeria Quimica, Universitat Rovira i Virgili, Av. Països Catalans 26, 43007 Tarragona, Catalonia, Spain; German Federal Institute for Risk Assessment (BfR), Berlin, Germany.
None:
Adverse Outcome Pathways (AOPs) provide a structured framework for linking mechanistic events across biological organization levels, supporting chemical hazard identification and regulatory decision-making in Next-Generation Risk Assessment (NGRA). However, AOP development remains labor-intensive, requiring extensive literature searching and expert review to identify relevant events and supporting evidence. Existing text mining tools often operate on limited datasets, lack interactive capabilities, and miss contextually relevant studies. To address these challenges, we present S2CIE (Semantic & Syntactic Context-based Information Extraction), an interactive, real-time platform for extracting mechanistic information from biomedical literature. S2CIE annotates PubMed abstracts (32 million) at the word level with grammatical, entity-type, and dependency annotations, enabling custom extraction rules based on syntactic patterns, and employ semantic retrieval based on user specific query. The system supports near real-time querying and integrates entity recognition and visual exploration tools. We demonstrate S2CIE's utility through four case studies. First, we identified 110 chemicals linked to liver steatosis/cholestasis with 98.79% precision, extracting chemical and PPAR (peroxisome proliferator-activated receptors) interactions as molecular initiating events. Second enrichment analysis of literature derived genes and successful mapping with AOPs. Third, comparative analysis against AOP-HelpFinder for key event relationships in AOP 220 showed 42.2% increased evidence capture (1,614 vs 1,135 abstracts) with 99% reduced retrieval time. Fourth, large-scale extraction of post-translational modification events demonstrated domain-agnostic applicability beyond toxicology. S2CIE accelerates AOP evidence gathering, while maintaining transparency and auditability essential for regulatory application. S2CIE is available as open source through an API and as web application at https://dev.s2cie.insilicohub.org/.
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