{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,27]],"date-time":"2026-08-27T08:21:50Z","timestamp":1787818910507,"version":"build-2784847793"},"reference-count":49,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2026,8,27]],"date-time":"2026-08-27T00:00:00Z","timestamp":1787788800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["32470667"],"award-info":[{"award-number":["32470667"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"award":["32470667"],"award-info":[{"award-number":["32470667"]}],"id":[{"id":"https:\/\/ror.org\/01h0zpd94","id-type":"ROR","asserted-by":"publisher"}]},{"name":"National High Level Hospital Clinical Research Funding","award":["2023-PUMCH-E-008"],"award-info":[{"award-number":["2023-PUMCH-E-008"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Genes"],"abstract":"<jats:p>Background\/Objectives: Genetic and chemical perturbation experiments provide a systematic approach to investigate cellular responses. Large-scale resources such as Connectivity Map (CMap) contain extensive transcriptomic perturbation signatures that support functional interpretation and perturbation retrieval. However, existing access to these resources mainly relies on structured inputs, making it challenging to connect natural-language perturbation questions with experimental evidence. Methods: To address this challenge, we developed PxFquery, an evidence-grounded tool that enables natural-language exploration of large-scale perturbation resources. PxFquery uses an LLM-assisted workflow to interpret biological questions and organize responses based on retrieved perturbation evidence. It converts over 500,000 CMap\/LINCS perturbation signatures into a compact functional response space and supports bidirectional perturbation-function queries. Results: Despite the sparse perturbation coverage of CMap (5.9%), PxFquery integrated related perturbation evidence and improved access to perturbation resources. Across evaluated genetic and chemical perturbation-to-function and function-to-perturbation queries, PxFquery outputs showed closer agreement with experimental reference rankings than direct and PubMed-augmented LLM approaches (paired Wilcoxon tests; p &lt; 0.05). Functional response representation reduced storage requirements to 0.068\u20130.24% of the original resources and enabled lightweight deployment through a Python package (v0.5.29), website, and AI workflow interfaces. Conclusions: PxFquery provides a natural-language interface for exploring large-scale perturbation resources while maintaining connections to experimental evidence. It lowers the barrier to accessing these resources and enables their integration into diverse AI workflows.<\/jats:p>","DOI":"10.3390\/genes17091014","type":"journal-article","created":{"date-parts":[[2026,8,27]],"date-time":"2026-08-27T08:02:27Z","timestamp":1787817747000},"page":"1014","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["PxFquery: A Bioinformatics Tool for Large Language Model-Assisted Functional Analysis of Large-Scale Perturbation Signatures"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9682-2724","authenticated-orcid":false,"given":"Jun","family":"Cao","sequence":"first","affiliation":[{"name":"State Key Laboratory of Complex, Severe, and Rare Diseases, Center for Bioinformatics, National Infrastructures for Translational Medicine, Institute of Clinical Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoyue","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Complex, Severe, and Rare Diseases, Center for Bioinformatics, National Infrastructures for Translational Medicine, Institute of Clinical Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,8,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1929","DOI":"10.1126\/science.1132939","article-title":"The Connectivity Map: Using Gene-Expression Signatures to Connect Small Molecules, Genes, and Disease","volume":"313","author":"Lamb","year":"2006","journal-title":"Science"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1437","DOI":"10.1016\/j.cell.2017.10.049","article-title":"A Next Generation Connectivity Map: L1000 Platform and the First 1,000,000 Profiles","volume":"171","author":"Subramanian","year":"2017","journal-title":"Cell"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"180117","DOI":"10.1038\/sdata.2018.117","article-title":"Sustainable Data and Metadata Management at the BD2K-LINCS Data Coordination and Integration Center","volume":"5","author":"Stathias","year":"2018","journal-title":"Sci. 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