Faculty

Robert Babak Faryabi, Ph.D.

Associate Professor of Pathology and Laboratory Medicine

Department: Pathology and Laboratory Medicine

Graduate Group Affiliations

Contact information

Room 553 BRB II/III, 421 Curie Boulevard
Philadelphia, PA 19104

Office: (215)573-8220

Email:
faryabi@pennmedicine.upenn.edu

Publications

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Education:
BSc (Electrical and Computer Engineering)
Sharif University of Technology, Tehran, Iran, 1995.
MSc (Electrical and Computer Engineering)
Sharif University of Technology, Tehran, Iran, 1997.
PhD (Computational Biology)
Texas A&M University, College Station, TX, 2009.

Links
Search PubMed for articles
Lab Website

Permanent link

> Perelman School of Medicine > Faculty > Details

Description of Clinical Expertise

Cancer Genomics

Description of Research Expertise

The overarching goal of our lab is to advance the mechanistic understanding of human cancer genome architecture and regulation. The lab expertise in chromatin, cancer, and computational biology allows us to deploy multidisciplinary approaches to rigorously define the cause-and-effect relationship between transcriptional regulators, chromatin organization, and gene expression in cancer. Current projects in the lab focuses on lymphoma and breast cancer and explore: i) how epigenetic control of gene expression is disrupted, ii) how transcriptional dependencies can develop, and iii) how heterogeneity and plasticity of transcriptional dependencies enable drug resistance in these cancers.

More details on the Faryabi Lab website https://faryabilab.com/

Selected Publications

Zhou Y, Jay A, Burget N, Friedrich T, Yoon S, Alsing J, Nir G, Grosschedl R, Vahedi G, Faryabi RB.: Lineage-determining transcription factors constrain cohesin to drive multi-enhancer oncogene regulation. Nat Cell Biol Dec 2025.

Abedi M, Rai P, Zhou Y, Liu C, Johnson I, Chandra A, Fasolino M, Rostami S, Wang W, Min Z, Li Y, Yu M, Jay A, Lian V, Silverman M, Kaestner KH, Naji A, Faryabi RB, Vahedi G.: Joint profiling of gene expression and chromatin accessibility in pancreatic lymph nodes and spleens in human type 1 diabetes. Sci Immunol 10: eadz0472, Nov 2025.

Zhou Y, Sheng Y, Hu D, Jay A, Vahedi G, Faryabi RB.: OLIVE provides rapid visualization and analysis of chromatin tracing experiments. Cell Rep Methods 5: 101209, Nov 2025.

Jafari H, Brown-Burke F, Pray B, Sloan S, Helmig-Mason J, Hout I, Leon S, Long M, Chan WK, Hanel W, Corps K, Leshchenko VV, Edwards D, Prakash Shukla R, Reci S, Vaddi K, Scherle P, Collier P, La Ferlita A, Singh S, Distefano R, Lapalombella R, Sehgal L, Faryabi RB, Meydan C, Mason CE, Baiocchi RA, Parekh S, Alinari L.: The Novel Immunocompetent Eµ-SOX11CCND1 Mouse Model Phenotypically and Molecularly Resembles Human Mantle Cell Lymphoma. Clin Cancer Res 31: 4571-4585, Nov 2025.

Jay A*, Zhou Y*, Yoon S, Abeje BN, Chandra A, Wald J, Raj A, Faryabi RB#, Vahedi G#: Single-allele chromatin tracing reveals genomic clustering of paralogous transcription factors as a mechanism for developmental robustness in T Cells. bioRxiv June 2025.

Bigdeli A, Chandrashekar DS, Chitturi A, Rushton C, Mackinnon AC, Segal J, Harada S, Sacan A, Faryabi RB: Azurify integrates cancer genomics with machine learning to classify the clinical significance of somatic variants. bioRxiv April 2025.

Perlman BS, Burget NG, Zhou Y, Schwartz GW, Petrovic J, Modrusan Z, Faryabi RB: Enhancer-promoter hubs organize transcriptional networks promoting oncogenesis and drug resistance. Nature Communications 15(1), September 2024.

Zhao J, Zhou Y, Tzelepis I, Burget NG, Shi J, Faryabi RB: Oncogenic transcription factors instruct promoter-enhancer hubs in individual triple negative breast cancer cells. Science Advances 10(22), August 2024.

Mongia A, Zohora FT, Burget NG, Zhou Y, Saunders DC, Wang YJ, Brissova M, Powers AC, Kaestner KH, Vahedi G, Naji A, Schwartz GW, Faryabi RB: AnnoSpat annotates cell types and quantifies cellular arrangements from spatial proteomics. Nature Communications 15(1), May 2024.

Patil AR, Schug J, Liu C, Lahori D, Descamps HC; Human Pancreas Analysis Consortium; Naji A, Kaestner KH, Faryabi RB, Vahedi G.: Modeling type 1 diabetes progression using machine learning and single-cell transcriptomic measurements in human islets. Cell Reports Medicine 5(5), May 2024.