Kirill Veselkov
Assistant Professor AdjunctCards
About
Research
Publications
Featured Publications
Identifying nutraceutical targets to treat polycystic ovary syndrome using graph representation learning
Hanassab S, Southern J, Olabode A, Laponogov I, Bronstein M, Comninos A, Heinis T, Abbara A, Izzi-Engbeaya C, Veselkov K, Dhillo W. Identifying nutraceutical targets to treat polycystic ovary syndrome using graph representation learning. Npj Women's Health 2025, 3: 68. PMID: 41341431, PMCID: PMC12669042, DOI: 10.1038/s44294-025-00117-4.Peer-Reviewed Original ResearchThe Helicobacter pylori AI-clinician harnesses artificial intelligence to personalise H. pylori treatment recommendations
Higgins K, Nyssen O, Southern J, Laponogov I, Veselkov D, Gisbert J, Kanonnikoff T, Veselkov K. The Helicobacter pylori AI-clinician harnesses artificial intelligence to personalise H. pylori treatment recommendations. Nature Communications 2025, 16: 6472. PMID: 40659612, PMCID: PMC12259899, DOI: 10.1038/s41467-025-61329-5.Peer-Reviewed Original ResearchOptimizing Ingredient Substitution Using Large Language Models to Enhance Phytochemical Content in Recipes
Rita L, Southern J, Laponogov I, Higgins K, Veselkov K. Optimizing Ingredient Substitution Using Large Language Models to Enhance Phytochemical Content in Recipes. Machine Learning And Knowledge Extraction 2024, 6: 2738-2752. DOI: 10.3390/make6040131.Peer-Reviewed Original ResearchCombinatorial prediction of therapeutic perturbations using causally inspired neural networks
Gonzalez G, Lin X, Herath I, Veselkov K, Bronstein M, Zitnik M. Combinatorial prediction of therapeutic perturbations using causally inspired neural networks. Nature Biomedical Engineering 2025, 10: 1008-1025. PMID: 40925962, PMCID: PMC13190336, DOI: 10.1038/s41551-025-01481-x.Peer-Reviewed Original ResearchFoundational Models for Pathology and Endoscopy Images: Application for Gastric Inflammation
Kerdegari H, Higgins K, Veselkov D, Laponogov I, Polaka I, Coimbra M, Pescino A, Leja M, Dinis-Ribeiro M, Kanonnikoff T, Veselkov K. Foundational Models for Pathology and Endoscopy Images: Application for Gastric Inflammation. Diagnostics 2024, 14: 1912. PMID: 39272697, PMCID: PMC11394237, DOI: 10.3390/diagnostics14171912.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsGenomic-driven nutritional interventions for radiotherapy-resistant rectal cancer patient
Southern J, Gonzalez G, Borgas P, Poynter L, Laponogov I, Zhong Y, Mirnezami R, Veselkov D, Bronstein M, Veselkov K. Genomic-driven nutritional interventions for radiotherapy-resistant rectal cancer patient. Scientific Reports 2023, 13: 14862. PMID: 37684345, PMCID: PMC10491580, DOI: 10.1038/s41598-023-41833-8.Peer-Reviewed Original ResearchAlzheimer’s disease: using gene/protein network machine learning for molecule discovery in olive oil
Rita L, Laponogov I, Gonzalez G, Veselkov D, Pratico D, Aalizadeh R, Thomaidis N, Thompson D, Vasiliou V, Veselkov K. Alzheimer’s disease: using gene/protein network machine learning for molecule discovery in olive oil. Human Genomics 2023, 17: 57. PMID: 37420280, PMCID: PMC10327379, DOI: 10.1186/s40246-023-00503-6.Peer-Reviewed Original ResearchDeep learning to detect macular atrophy in wet age-related macular degeneration using optical coherence tomography
Wei W, Southern J, Zhu K, Li Y, Cordeiro M, Veselkov K. Deep learning to detect macular atrophy in wet age-related macular degeneration using optical coherence tomography. Scientific Reports 2023, 13: 8296. PMID: 37217770, PMCID: PMC10203346, DOI: 10.1038/s41598-023-35414-y.Peer-Reviewed Original ResearchPredicting anticancer hyperfoods with graph convolutional networks
Gonzalez G, Gong S, Laponogov I, Bronstein M, Veselkov K. Predicting anticancer hyperfoods with graph convolutional networks. Human Genomics 2021, 15: 33. PMID: 34099048, PMCID: PMC8182908, DOI: 10.1186/s40246-021-00333-4.Peer-Reviewed Original ResearchAuto-deconvolution and molecular networking of gas chromatography–mass spectrometry data
Aksenov AA, Laponogov I, Zhang Z, Doran SLF, Belluomo I, Veselkov D, Bittremieux W, Nothias LF, Nothias-Esposito M, Maloney KN, Misra BB, Melnik AV, Smirnov A, Du X, Jones KL, Dorrestein K, Panitchpakdi M, Ernst M, van der Hooft JJJ, Gonzalez M, Carazzone C, Amézquita A, Callewaert C, Morton JT, Quinn RA, Bouslimani A, Orio AA, Petras D, Smania AM, Couvillion SP, Burnet MC, Nicora CD, Zink E, Metz TO, Artaev V, Humston-Fulmer E, Gregor R, Meijler MM, Mizrahi I, Eyal S, Anderson B, Dutton R, Lugan R, Boulch PL, Guitton Y, Prevost S, Poirier A, Dervilly G, Le Bizec B, Fait A, Persi NS, Song C, Gashu K, Coras R, Guma M, Manasson J, Scher JU, Barupal DK, Alseekh S, Fernie AR, Mirnezami R, Vasiliou V, Schmid R, Borisov RS, Kulikova LN, Knight R, Wang M, Hanna GB, Dorrestein PC, Veselkov K. Auto-deconvolution and molecular networking of gas chromatography–mass spectrometry data. Nature Biotechnology 2020, 39: 169-173. PMID: 33169034, PMCID: PMC7971188, DOI: 10.1038/s41587-020-0700-3.Peer-Reviewed Original Research