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Institute of Cell Engineering
733 N. Broadway
Baltimore, MD 21287
Hybrid experimental/ computational lab studying gene regulatory networks in development, stem cell engineering, and cancer
My lab is an interdisciplinary group that devises and experimentally tests computational tools to explore cell type identity and its molecular underpinnings. A unifying component of our research is the gene regulatory network (GRN). GRNs are programs encoded in the genome that define the set of regulatory relationships among genes and gene products. GRNs govern the cell’s transcriptional output both at steady state and in response to perturbations, and thus are major molecular determinants of cell-type identity. We develop new algorithms to reconstruct GRNs, to infer their dynamics (i.e. how they are established during development), and to model intercellular regulatory networks. All of our computational efforts are grounded by the criteria that the resulting hypotheses be experimentally testable, and we use hematopoietic stem cells and articular chondrocytes from both mice and those derived in vitro from pluripotent stem cells to experimentally to inform and to test our algorithms. A central, long-term goal of my lab is to devise generally applicable computational approaches that will enable directing cell fate decisions with precision and efficiency for purposes of regenerative medicine and disease modeling..
Multi-scale cellular engineering: From molecules to organ-on-a-chip. Huang NF, Chaudhuri O, Cahan P, Wang A, Engler AJ, Wang Y, Kumar S, Khademhosseini A, Li S. APL Bioengineering.2020 Mar 3;4(1). PMID: 32161833
SingleCellNet: A Computational Tool to Classify Single Cell RNA-Seq Data Across Platforms and Across Species. Tan Y and Cahan P., Cell Systems. 2019 Jul 17. pii: S2405-4712(19)30199-1. PMID: 31377170
Cell Fate Engineering Tools for iPSC Disease Modeling. Lo EKW, Cahan P. Methods Mol Biol. 2019;1975:427-454. PMID: 31062321
A single cell transcriptional portrait of embryoid body differentiation and comparison to progenitors of the developing embryo Spangler, A, Su, E, Craft, AM, Cahan P Stem Cell Research. 2018 Aug;31:201-215. PMID: 30118958
Programming Morphogenesis through Systems and Synthetic Biology Velazquez JJ, Su E, Cahan P, Ebrahimkhani MR Trends in Biotechnology. 2017 Dec 08 pii: S0167-7799(17)30301-3 PMID: 29229492
Radley AH, Schwab RM, Tan Y, Kim J, Lo EKW, Cahan P. Assessment of engineered cells using CellNet and RNA-seq. Nature Protocols. 2017 May;12(5):1089-1102. PMID: 28448485
Kumar P., Tan Y., Cahan P., 2017, Understanding development and stem cells using single-based analyses of gene expression, Development. 144(1):17-32
Bian Q, Cahan P. Computational Tools for Stem Cell Biology. Trends in Biotechnology. 2016 Jun. 10.1016/j.tibtech.2016.05.010.
Kumar RM*, Cahan P*, Shalek A, Satija R, DaleyKeyser A, Li H, Zhang J, Pardee K, Gennert D, Trombetta JJ, Ferrante TC, Regev A, Daley GQ, and Collins JJ. Deconstructing transcriptional heterogeneity in pluripotent stem cells. Nature. 2014 Dec 4;516(7529):56–61.
Cahan P*, Li H*, Morris SA*, Lummertz da Rocha E, Daley GQ, Collins JJ. CellNet: Network Biology Applied to Stem Cell Engineering. Cell. 2014 Aug 14;158(4):903–15.
Morris SA*, Cahan P*, Li H*, Zhao AM, San Roman AK, Shivdasani RA, Collins JJ, Daley GQ. Dissecting Engineered Cell Types and Enhancing Cell Fate Conversion via CellNet. Cell. 2014 Aug 14;158(4):889–902.
Cahan P, Daley GQ. Origins and implications of pluripotent stem cell variability and heterogeneity. (2013). Nature Reviews Molecular Cell Biology 14:357–68.
McKinney-Freeman S*, Cahan P*, Li H*, Lacadie SA, Huang HT, Curran M, Loewer S, Naveiras O, Kathrein KL, Konantz M, Langdon EM, Lengerke C, Zon LI, Collins JJ, Daley GQ. The transcriptional landscape of hematopoietic stem cell ontogeny. Cell Stem Cell. 2012 Nov 2;11(5):701–14.
Cahan P, Li Y, Izumi M, Graubert TA. The impact of copy number variation on local gene expression in mouse hematopoietic stem and progenitor cells. Nature Genetics. 2009 Apr;41(4):430–7. *Denotes equal contribution