733 N. Broadway
Baltimore, MD 21287
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..
Peng D, Gleyzer R, Tai WH, Kumar P, Bian Q, Isaacs B, da Rocha EL, Cai S,
DiNapoli K, Huang FW, Cahan P. Evaluating the transcriptional fidelity of cancer
models. Genome Med. 2021 Apr 29;13(1):73. doi: 10.1186/s13073-021-00888-w. PMID:
33926541; PMCID: PMC8086312.
Cahan P, Cacchiarelli D, Dunn SJ, Hemberg M, de Sousa Lopes SMC, Morris SA,
Rackham OJL, Del Sol A, Wells CA. Computational Stem Cell Biology: Open
Questions and Guiding Principles. Cell Stem Cell. 2021 Jan 7;28(1):20-32. doi:
10.1016/j.stem.2020.12.012. PMID: 33417869; PMCID: PMC7799393.
Bian Q, Cheng YH, Wilson JP, Su EY, Kim DW, Wang H, Yoo S, Blackshaw S, Cahan
P. A single cell transcriptional atlas of early synovial joint development.
Development. 2020 Jul 20;147(14):dev185777. doi: 10.1242/dev.185777. PMID:
32580935; PMCID: PMC7390639.
Tan Y, Cahan P. SingleCellNet: A Computational Tool to Classify Single Cell
RNA-Seq Data Across Platforms and Across Species. Cell Syst. 2019 Aug
28;9(2):207-213.e2. doi: 10.1016/j.cels.2019.06.004. Epub 2019 Jul 31. PMID:
31377170; PMCID: PMC6715530.
Kumar P., Tan Y., Cahan P., 2017, Understanding development and stem cells using single-based analyses of gene expression, Development. 144(1):17-32