{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T20:03:07Z","timestamp":1792785787879,"version":"4.5.0"},"reference-count":50,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T00:00:00Z","timestamp":1790035200000},"content-version":"vor","delay-in-days":264,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"ONTOX"},{"name":"European Union\u2019s Horizon 2020 Research and Innovation","award":["963845"],"award-info":[{"award-number":["963845"]}],"id":[{"id":"https:\/\/ror.org\/001aqnf71","id-type":"ROR","asserted-by":"crossref"}]},{"name":"European Union\u2019s Horizon Europe Framework","award":["HEU\/2022\u20132027"],"award-info":[{"award-number":["HEU\/2022\u20132027"]}]},{"name":"ERC INSTant-CARMa","award":["101088919"],"award-info":[{"award-number":["101088919"]}]},{"name":"Netherlands Organization for Scientific Research","award":["1292.19.272"],"award-info":[{"award-number":["1292.19.272"]}],"id":[{"id":"https:\/\/ror.org\/04jsz6e67","id-type":"ROR","asserted-by":"crossref"}]},{"name":"German Research Foundation","award":["2901\/1]"],"award-info":[{"award-number":["2901\/1]"]}],"id":[{"id":"https:\/\/ror.org\/018mejw64","id-type":"ROR","asserted-by":"crossref"}]},{"name":"ELIXIR Luxembourg Node"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,1,7]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Summary: As biomedical knowledge keeps growing, resources storing available information multiply and grow in size and complexity. Such resources can be in the format of molecular interaction maps, which represent cellular and molecular processes under normal or pathological conditions. However, these maps can be complex and hard to navigate, especially to novice users. Large language models (LLMs), particularly in the form of agentic frameworks, have emerged as a promising technology to support this exploration. In this article, we describe a user-driven process of prototyping, development, and user testing of Llemy, an LLM-based system for exploring these molecular interaction maps. By involving domain experts from the very first prototyping in the form of a hackathon and collecting both fine-grained and general feedback on more refined versions, we were able to evaluate the perceived utility and quality of the developed system, in particular for summarizing maps and pathways, as well as prioritize the development of future features. We recommend continued user-driven development and benchmarking to keep the community engaged. This will also facilitate the transition towards open-weight LLMs to support the needs of the open research environment in an ever-changing technology landscape.<\/jats:p>","DOI":"10.1093\/bioadv\/vbag277","type":"journal-article","created":{"date-parts":[[2026,9,18]],"date-time":"2026-09-18T18:29:15Z","timestamp":1789756155000},"source":"Crossref","is-referenced-by-count":0,"title":["User-driven development and evaluation of an agentic framework for analysis of large pathway diagrams"],"prefix":"10.1093","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8185-5913","authenticated-orcid":false,"given":"Marie","family":"Corradi","sequence":"first","affiliation":[{"name":"Innovative Testing in Life Sciences and Chemistry, HU\u2014University of Applied Sciences Utrecht , 3584 CS 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