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To address this problem, computational approaches that generate machine-readable representations of scientific findings in the form of knowledge graphs have been developed. These representations can integrate different types of experimental data from multiple papers and biological knowledge bases in a unifying data model, providing a complementary method to manual review for interacting with published knowledge. The Gene Ontology Consortium (GOC) has created a semantic modelling framework that extends individual functional gene annotations to structured descriptions of causal networks representing biological processes (Gene Ontology\u2013Causal Activity Modelling, or GO\u2013CAM). In this study, we explored whether the GO\u2013CAM framework could represent knowledge of the causal relationships between environmental inputs, neural circuits and behavior in the model nematode <jats:italic>C. elegans<\/jats:italic> [<jats:italic>C. elegans<\/jats:italic> Neural\u2013Circuit Causal Activity Modelling (<jats:italic>Ce<\/jats:italic>N\u2013CAM)]<jats:italic>.<\/jats:italic> We found that, given extensions to several relevant ontologies, a wide variety of author statements from the literature about the neural circuit basis of egg-laying and carbon dioxide (CO<jats:sub>2<\/jats:sub>) avoidance behaviors could be faithfully represented with <jats:italic>Ce<\/jats:italic>N\u2013CAM. Through this process, we were able to generate generic data models for several categories of experimental results. We also discuss how semantic modelling may be used to functionally annotate the <jats:italic>C. elegans<\/jats:italic> connectome. Thus, Gene Ontology-based semantic modelling has the potential to support various machine-readable representations of neurobiological knowledge.<\/jats:p>\n                <jats:p><jats:bold>Graphical Abstract<\/jats:bold><\/jats:p>","DOI":"10.1186\/s40708-023-00208-5","type":"journal-article","created":{"date-parts":[[2023,11,10]],"date-time":"2023-11-10T16:02:54Z","timestamp":1699632174000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Semantic representation of neural circuit knowledge in Caenorhabditis elegans"],"prefix":"10.1186","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1777-0987","authenticated-orcid":false,"given":"Sharan J.","family":"Prakash","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1706-4196","authenticated-orcid":false,"given":"Kimberly M.","family":"Van Auken","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7476-6306","authenticated-orcid":false,"given":"David P.","family":"Hill","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7699-0173","authenticated-orcid":false,"given":"Paul W.","family":"Sternberg","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2023,11,10]]},"reference":[{"key":"208_CR1","doi-asserted-by":"publisher","first-page":"450","DOI":"10.1038\/nrg2102","volume":"8","author":"U Alon","year":"2007","unstructured":"Alon U (2007) Network motifs: Theory and experimental approaches. 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