User-driven development and evaluation of an agentic framework for analysis of large pathway diagrams

Clicks: 12
ID: 329485
2026
Free PDF
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Emerging

Ranked #152 of 172 articles by views in Bioinformatics advances

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 172 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
Abstract 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 summarising maps and pathways, as well as prioritise 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.
Reference Key
openalex_W7214062598 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Marie Corradi, Ivo Djidrovski, Luiz Carlos Maia Ladeira, Bernard Staumont, Anouk Verhoeven, Julen Sanz-Serrano, Adrien Rougny, Ahmad Vaez, Ahmed Abdelmonem Hemedan, Alexander Mazein, Anna Niarakis, Arthur C. Silva, Charles Auffray, Egon Willighagen, Eliška Kuchovská, Falk Schreiber, Irina Balaur, Laurence Calzone, Lisa R. Matthews, Lorenzo Veschini, Marc E. Gillespie, Martina Kutmon, Matthias König, Matti Hoch, Noriko F. Hiroi, Oxana Lopata, Pierre Klemmer, Rupert W. Overall, Tim Hofer, Venkata Satagopam, Reinhard Schneider, Marc Teunis, Liesbet Geris, Marek Ostaszewski
Are you one of these authors? Claim your profile
Journal Bioinformatics advances
Year 2026
DOI
10.1093/bioadv/vbag277
URL
https://doi.org/10.1093/bioadv/vbag277
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.