We are a diverse, interdisciplinary team who likes to tackle important questions in systems medicine by developing and using novel machine learning algorithms. Our ultimate goal is to identify risk factors and mechanisms affecting aging and contributing to the onset and progression of chronic diseases and cancer. We also develop predictive methods and tools that can directly improve health. We use probabilistic graphical models and other machine learning methods to integrate and mine high-dimensional, multi-modal biomedical data and to investigate biological processes pertinent to health and disease.
Web server: https://db.cs.pitt.edu/causalmgm/
WordCloud of Benos Lab research
From titles and abstracts of Benos’ group 2020-2022.
Representative Recent publications
- H. Mao*, M. Jia*, M. Di*, E. Valenzi, X.T. Cai, R. Lafyatis, K. Zhang, P.V. Benos, “HALO: Hierarchical Causal Modeling for Single Cell Multi-Omics Data”, Nature Communications (2025) 16:8892. [Abstract] [Article] [bioRxiv] [GitHub]
- M. Jia, H. Mao, M. Zhou, Y.-C. Chen, P.V. Benos, “LaGrACE: Estimating gene program dysregulation with latent regulatory network”, Molecular Systems Biology (2025) 21:1263-1281. [Abstract] [Article] [bioRxiv] [GitHub]
- D. Yuan, M.L. McKeague, V.K. Raghu, R.E. Schoen, O.J. Finn#, P.V. Benos#, “Immune cell transcriptional profiles from pre-vaccination peripheral blood predict immune response to preventative MUC1 cancer vaccine”, European Journal of Cancer, (2025), 228:115685. [Abstract] [Article] [bioRxiv]
- T.C. Lovelace, M.H. Ryu, M. Jia, P. Castaldi, F.C. Sciurba, C.P. Hersh, P.V. Benos, “Development and validation of a mortality risk prediction model for chronic obstructive pulmonary disease: a cross-sectional study using probabilistic graphical modelling”, eClinicalMedicine (2024) 75:102786. [Abstract] [Article] [medRxiv]
- R.W. Gregg, C.M. Karoleski, E.K. Silverman, F.C. Sciurba, D.L. DeMeo, P.V. Benos, “Identification of Factors Directly Linked to Incident Chronic Obstructive Pulmonary Disease: A Causal Graph Modeling Study”, PLoS Medicine (2024) 21:e1004444. [Abstract] [Article]
- W. Zeng, A. Thatayatikom, N. Winn, T.C. Lovelace, I. Bhattacharyya, T. Schrepfer, A. Shah, R. Gonik, P.V. Benos#, S. Cha#, “The novel Florida Scoring System for stratifying children suspected of Sjögren’s disease: findings from the first data-driven cross-sectional study applied to a rare pediatric cohort”. Lancet Rheumatology (2024) 6:e279-e290. [Abstract] [Article]
News & Highlights
Robert and Shaira have Abstracts accepted for…
Robert will have an oral presentation at the upcoming 2026 American Thoracic Society conference (ATS2026): Oral presentation Session: B101 …
Marissa has a collaborative paper accepted in JCI…
Congratulations to our group member, Marissa Di, for the acceptance of her collaborative paper in JCI Insight. The paper is entitled “Alpha…
Minxue has a first co-author paper accepted in…
Congratulations to our group member, Minxue Jia, for the acceptance of his first co-author paper in European Respiratory Journal. His paper is…
