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Article Abstract
Motivation: Lipids play crucial roles in various biological functions and diseases. However, a gap exists in databases providing information of lipids functions based on curated information. Consequently, LipidFun is purposed as the first lipid function database with sentence-level evidence detailing lipid-related phenotypes and biological functions.
Results: Potential lipid functions were extracted from the biomedical literature using natural language processing techniques, with accuracy and reliability ensured through manual curation by four domain experts. LipidFun constructs classification systems for lipids, biological functions, and phenotypes for named entity recognition. Sentence-level evidence is extracted to highlight connections to lipid-associated biological processes and diseases. Integrating these classification systems and a large amount of sentence-level evidence allows LipidFun to provide an overview of lipid-phenotype and lipid-biological function associations through concise visualizations. Overall, LipidFun unravels the relationships between lipids and biological mechanisms, underscoring their overarching influence on physiological processes.
Availability And Implementation: LipidFun is available at https://lipidfun.bioinfomics.org/.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11974499 | PMC |
| http://dx.doi.org/10.1093/bioinformatics/btaf110 | DOI Listing |
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