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.
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
Tyler has a first author paper accepted in…
Congratulations to our group member (now alumnus), Tyler Lovelace, for the acceptance of his paper in the journal GigaScience. His paper is…
Congratulations Dr. Di (thesis defense)
Congratulations to Marissa for defending her PhD thesis, entitled “Identifying regulatory mechanisms in biological systems using nonlinear causal…
Mark has a first author paper accepted in…
Congratulations to our group member (now alumnus), Mark Ebeid, for the acceptance of his paper in the RECOMB-CG conference. His paper is entitled…