{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T11:38:13Z","timestamp":1771501093493,"version":"3.50.1"},"reference-count":22,"publisher":"Oxford University Press (OUP)","issue":"12","license":[{"start":{"date-parts":[[2021,1,8]],"date-time":"2021-01-08T00:00:00Z","timestamp":1610064000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"name":"Ramalingaswami Re-entry Fellowship","award":["BT\/RLF\/Re-entry\/36\/2019"],"award-info":[{"award-number":["BT\/RLF\/Re-entry\/36\/2019"]}]},{"DOI":"10.13039\/501100001407","name":"Department of Biotechnology","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001407","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100019473","name":"Ministry of Science & Technology","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100019473","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Govt. of India"},{"name":"Science and Engineering Research Board Fellowship","award":["SRG\/2020\/000232"],"award-info":[{"award-number":["SRG\/2020\/000232"]}]},{"name":"Indraprastha Institute of Information Technology-Delhi"},{"DOI":"10.13039\/501100000303","name":"INSPIRE","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100000303","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100010218","name":"Department of Science & Technology","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100010218","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,7,19]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Summary<\/jats:title>\n                  <jats:p>Machine Learning-based techniques are emerging as state-of-the-art methods in chemoinformatics to selectively, effectively and speedily identify biologically relevant molecules from large databases. So far, a multitude of such techniques have been proposed, but unfortunately due to their sparse availability, and the dependency on high-end computational literacy, their wider adaptation faces challenges, at least in the context of G-Protein Coupled Receptors (GPCRs)-associated chemosensory research. Here, we report Machine-OlF-Action (MOA), a user-friendly, open-source computational framework, that utilizes user-supplied SMILES (simplified molecular input line entry system) of the chemicals, along with their activation status, to synthesize classification models. MOA integrates a number of popular chemical databases collectively harboring approximately 103 million chemical moieties. MOA also facilitates customized screening of user-supplied chemical datasets. A key feature of MOA is its ability to embed molecules based on the similarity of their local neighborhood, by utilizing a state-of-the-art model interpretability framework LIME. We demonstrate the utility of MOA in identifying previously unreported agonists for human and mouse olfactory receptors OR1A1 and MOR174-9 by leveraging the chemical features of their known agonists and non-agonists. In summary, here we develop an ML-powered software playground for performing supervisory learning tasks involving chemical compounds.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>MOA is available for Windows, Mac and Linux operating systems. It\u2019s accessible at (https:\/\/ahuja-lab.in\/). Source code, user manual, step-by-step guide and support is available at GitHub (https:\/\/github.com\/the-ahuja-lab\/Machine-Olf-Action). For results, reproducibility and hyperparameters, refer to Supplementary Notes.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Supplementary information<\/jats:title>\n                  <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btaa1104","type":"journal-article","created":{"date-parts":[[2020,12,29]],"date-time":"2020-12-29T12:20:45Z","timestamp":1609244445000},"page":"1769-1771","source":"Crossref","is-referenced-by-count":11,"title":["<i>Machine-OlF-Action<\/i>: a unified framework for developing and interpreting machine-learning models for chemosensory research"],"prefix":"10.1093","volume":"37","author":[{"given":"Anku","family":"Gupta","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, Indraprastha Institute of Information Technology-Delhi (IIIT-Delhi), Okhla, Phase III, New Delhi 110020, India"}]},{"given":"Mohit","family":"Choudhary","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Indraprastha Institute of Information Technology-Delhi (IIIT-Delhi), Okhla, Phase III, New Delhi 110020, India"}]},{"given":"Sanjay Kumar","family":"Mohanty","sequence":"additional","affiliation":[{"name":"Department of Computational Biology, Indraprastha Institute of Information Technology-Delhi (IIIT-Delhi), Okhla, Phase III, New Delhi 110020, India"}]},{"given":"Aayushi","family":"Mittal","sequence":"additional","affiliation":[{"name":"Department of Computational Biology, Indraprastha Institute of Information Technology-Delhi (IIIT-Delhi), Okhla, Phase III, New Delhi 110020, India"}]},{"given":"Krishan","family":"Gupta","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Indraprastha Institute of Information Technology-Delhi (IIIT-Delhi), Okhla, Phase III, New Delhi 110020, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9629-2532","authenticated-orcid":false,"given":"Aditya","family":"Arya","sequence":"additional","affiliation":[{"name":"Pathfinder Research and Training Foundation, 30\/7 and 8, Knowledge Park III , Greater Noida, Uttar Pradesh 201308, India"}]},{"given":"Suvendu","family":"Kumar","sequence":"additional","affiliation":[{"name":"Department of Computational Biology, Indraprastha Institute of Information Technology-Delhi (IIIT-Delhi), Okhla, Phase III, New Delhi 110020, India"}]},{"given":"Nikhil","family":"Katyayan","sequence":"additional","affiliation":[{"name":"Department of Computational Biology, Indraprastha Institute of Information Technology-Delhi (IIIT-Delhi), Okhla, Phase III, New Delhi 110020, India"}]},{"given":"Nilesh Kumar","family":"Dixit","sequence":"additional","affiliation":[{"name":"Department of Computational Biology, Indraprastha Institute of Information Technology-Delhi (IIIT-Delhi), Okhla, Phase III, New Delhi 110020, India"}]},{"given":"Siddhant","family":"Kalra","sequence":"additional","affiliation":[{"name":"Department of Computational Biology, Indraprastha Institute of Information Technology-Delhi (IIIT-Delhi), Okhla, Phase III, New Delhi 110020, India"}]},{"given":"Manshi","family":"Goel","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Indraprastha Institute of Information Technology-Delhi (IIIT-Delhi), Okhla, Phase III, New Delhi 110020, India"}]},{"given":"Megha","family":"Sahni","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Indraprastha Institute of Information Technology-Delhi (IIIT-Delhi), Okhla, Phase III, New Delhi 110020, India"}]},{"given":"Vrinda","family":"Singhal","sequence":"additional","affiliation":[{"name":"Department of Computational Biology, Indraprastha Institute of Information Technology-Delhi (IIIT-Delhi), Okhla, Phase III, New Delhi 110020, India"}]},{"given":"Tripti","family":"Mishra","sequence":"additional","affiliation":[{"name":"Pathfinder Research and Training Foundation, 30\/7 and 8, Knowledge Park III , Greater Noida, Uttar Pradesh 201308, India"}]},{"given":"Debarka","family":"Sengupta","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Indraprastha Institute of Information Technology-Delhi (IIIT-Delhi), Okhla, Phase III, New Delhi 110020, India"},{"name":"Department of Computational Biology, Indraprastha Institute of Information Technology-Delhi (IIIT-Delhi), Okhla, Phase III, New Delhi 110020, India"},{"name":"Centre for Artificial Intelligence, Indraprastha Institute of Information Technology , Okhla, Phase III, New Delhi 110020, India"},{"name":"Institute of Health and Biomedical Innovation, Queensland University of Technology , Brisbane, QLD 4001, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2837-9361","authenticated-orcid":false,"given":"Gaurav","family":"Ahuja","sequence":"additional","affiliation":[{"name":"Department of Computational Biology, Indraprastha Institute of Information Technology-Delhi (IIIT-Delhi), Okhla, Phase III, New Delhi 110020, India"}]}],"member":"286","published-online":{"date-parts":[[2021,1,8]]},"reference":[{"key":"2023051709461518200_btaa1104-B1","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1186\/1471-2105-14-106","article-title":"SMOTE for high-dimensional class-imbalanced data","volume":"14","author":"Blagus","year":"2013","journal-title":"BMC Bioinformatics"},{"key":"2023051709461518200_btaa1104-B2","doi-asserted-by":"crossref","first-page":"2235","DOI":"10.1021\/acs.jpclett.8b00633","article-title":"Agonists of G-protein-coupled odorant receptors are predicted from chemical features","volume":"9","author":"Bushdid","year":"2018","journal-title":"J. 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