Adam MacLean

Assistant Professor of Quantitative and Computational Biology
Pronouns He / Him / His Email macleana@usc.edu Office RRI 403H Office Phone (213) 740-7055

Research & Practice Areas

Systems biology; dynamical systems theory; statistical inference; computational methods for data analysis; dimensionality reduction

Education

  • Ph.D. Systems Biology, Imperial College London, 2014
  • M.S. Bioinformatics and Systems Biology, Imperial College London, 2010
  • B.S. Mathematical Physics, University of Edinburgh, 2009
  • Tenure Track Appointments

    • Assistant Professor of Biological Sciences, University of Southern California, 01/2019 –

    PostDoctoral Appointments

    • Research Associate, Imperial College London, 01/2015 – 08/2016
    • Research Associate, University of Oxford, 01/2014 – 01/2015
    • Postdoctoral Scholar, University of California, Irvine, 09/2016 – 12/2018
  • Summary Statement of Research Interests

    Research in our group focuses on developing mathematical and computational methods to study stem cell fate. Ultimately, we seek to derive a mechanistic theory for stem cell function in health and disease. Stem cells are essential for development and the regeneration of organs throughout our lifetimes. Diverse types of stem cells underpin these processes, yet they share essential characteristics, such as the ability to self renew, to dynamically respond to perturbations, and to robustly produce specialized tissue cells in noisy and heterogeneous environments. To shed light on these complex regulatory mechanisms, we build models and develop methods based in dynamical systems theory, statistical inference, high dimensional data analysis, and systems biology.

    Research Keywords

    Stem cells; signaling networks; cell fate decisions; single-cell analysis; development and regeneration; cancer

    Research Specialties

    Systems biology; dynamical systems theory; statistical inference; computational methods for data analysis; dimensionality reduction

  • Contracts and Grants Awarded

    • Computational methods to predict gene regulatory network dynamics and cell state, (NIH), Adam MacLean, $2,062,500, 09/2021 – 08/2026
    • CAREER: Inference of gene regulatory networks and cell dynamics that control stem cell fate, (NSF), Adam MacLean, $571,458, 03/2021 – 02/2026
  • Journal Article

    • Xiong, L., Liu, J., Han, S. Y., Koppitch, K., Guo, J. J., Rommelfanger, M., Miao, Z., Gao, F., Hallgrimsdottir, I. B., Pachter, L., Kim, J., MacLean, A. L., McMahon,Xiong, A. P., Liu, J., Han, S. Y., Koppitch, K., Guo, J. J., Rommelfanger, M., Miao, Z., Gao, F., Hallgrimsdottir, I. B., Pachter, L., Kim, J., MacLean, A. L., McMahon, A. P. (2023). Direct androgen receptor control of sexually dimorphic gene expression in the mammalian kidney. Developmental cell. PubMed Web Address
    • Coulis, G., Jaime, D., Guerrero-Juarez, C., Kastenschmidt, J. M., Farahat, P. K., Nguyen, Q., Pervolarakis, N., McLinden, K., Thurlow, L., Movahedi, S., Hughes, B. S., Duarte, J., Sorn, A., Montoya, E., Mozaffar, I., Dragan, M., Othy, S., Joshi, T., Hans, C. P., Kimonis, V., MacLean, A. L., Nie, Q., Wallace, L. M., Harper, S. Q., Mozaffar, T., Hogarth, M. W., Bhattacharya, S., Jaiswal, J. K., Golann, D. R., Su, Q., Kessenbrock, K., Stec, M., Spencer, M. J., Zamudio, J. R., Villalta,Coulis, S. A., Jaime, D., Guerrero-Juarez, C., Kastenschmidt, J. M., Farahat, P. K., Nguyen, Q., Pervolarakis, N., McLinden, K., Thurlow, L., Movahedi, S., Hughes, B. S., Duarte, J., Sorn, A., Montoya, E., Mozaffar, I., Dragan, M., Othy, S., Joshi, T., Hans, C. P., Kimonis, V., MacLean, A. L., Nie, Q., Wallace, L. M., Harper, S. Q., Mozaffar, T., Hogarth, M. W., Bhattacharya, S., Jaiswal, J. K., Golann, D. R., Su, Q., Kessenbrock, K., Stec, M., Spencer, M. J., Zamudio, J. R., Villalta, S. A. (2023). Single-cell and spatial transcriptomics identify a macrophage population associated with skeletal muscle fibrosis. Science advances. Vol. 9 (27), pp. eadd9984. PubMed Web Address
    • Wu, X., Wollman, R., MacLean,Wu, A. L., Wollman, R., MacLean, A. L. (2023). Single-cell Ca(2+) parameter inference reveals how transcriptional states inform dynamic cell responses. Journal of the Royal Society, Interface. Vol. 20 (203), pp. 20230172. PubMed Web Address
    • Roesch, E., Greener, J. G., MacLean, A. L., Nassar, H., Rackauckas, C., Holy, T. E., Stumpf, M. P. (2023). Julia for biologists. Nature methods. Vol. 20 (5), pp. 655-664. PubMed Web Address
    • Kreger, J., Roussos, E. T., MacLean, A. L. (2023). Myeloid-Derived Suppressor-Cell Dynamics Control Outcomes in the Metastatic Niche. Cancer immunology research. Vol. 11 (5), pp. 614-628. PubMed Web Address
    • MacLean, A. L. (2023). Voices carry. Nature chemical biology. Vol. 19 (5), pp. 540-541. PubMed Web Address
    • MacLean, A. L. (2022). Profiling intermediate cell states in high resolution. Cell reports methods. Vol. 2 (4), pp. 100204. PubMed Web Address
    • Suo, M., Rommelfanger, M. K., Chen, Y., Amro, E. M., Han, B., Chen, Z., Szafranski, K., Chakkarappan, S. R., Boehm, B. O., MacLean, A. L., Rudolph, K. L. (2022). Age-dependent effects of Igf2bp2 on gene regulation, function, and aging of hematopoietic stem cells in mice. Blood. Vol. 139 (17), pp. 2653-2665. PubMed Web Address
    • Rommelfanger, M. K., MacLean, A. L. (2021). A single-cell resolved cell-cell communication model explains lineage commitment in hematopoiesis. Development. Vol. 148 (24) PubMed Web Address
    • MacLean, A. L., Nie, Q. (2021). The diverse landscape of modeling in single-cell biology. Physical Biology. Vol. 18 (5) PubMed Web Address
    • Mitra, R., MacLean, A. L. (2021). RVAgene: Generative modeling of gene expression time series data. Bioinformatics (Oxford, England). PubMed Web Address
    • Bergman, D. R., Karikomi, M. K., Yu, M., Nie, Q., MacLean,Bergman, A. L., Karikomi, M. K., Yu, M., Nie, Q., MacLean, A. L. (2021). Modeling the effects of EMT-immune dynamics on carcinoma disease progression. Communications biology. Vol. 4 (1), pp. 983. PubMed Web Address
    • Tatarakis, D., Cang, Z., Wu, X., Sharma, P. P., Karikomi, M., MacLean, A. L., Nie, Q., Schilling, T. F. (2021). Single-cell transcriptomic analysis of zebrafish cranial neural crest reveals spatiotemporal regulation of lineage decisions during development. Cell reports. Vol. 37 (12), pp. 110140. PubMed Web Address
    • Wang, S., Drummond, M. L., Guerrero-Juarez, C. F., Tarapore, E., MacLean, A. L., Stabell, A. R., Wu, S. C., Gutierrez, G., That, B. T., Benavente, C. A., Nie, Q., Atwood, S. X. (2020). Single cell transcriptomics of human epidermis identifies basal stem cell transition states. Nature communications. Vol. 11 (1), pp. 4239. PubMed Web Address
    • Haensel, D., Jin, S., Sun, P., Cinco, R., Dragan, M., Nguyen, Q., Cang, Z., Gong, Y., Vu, R., MacLean, A. L., Kessenbrock, K., Gratton, E., Nie, Q., Dai, X. (2020). Defining Epidermal Basal Cell States during Skin Homeostasis and Wound Healing Using Single-Cell Transcriptomics. Cell reports. Vol. 30 (11), pp. 3932-3947.e6. PubMed Web Address
    • Wang, S., Karikomi, M., MacLean, A. L., Nie, Q. (2019). Cell lineage and communication network inference via optimization for single-cell transcriptomics. Nucleic Acids Research. pp. gkz204. PubMed Web Address
    • Haensel, D., Sun, P., MacLean, A. L., Ma, X., Zhou, Y., Stemmler, M. P., Brabletz, S., Berx, G., Plikus, M. V., Nie, Q., Brabletz, T., Dai, X. (2019). An Ovol2-Zeb1 transcriptional circuit regulates epithelial directional migration and proliferation. EMBO Rep. Vol. 20, pp. e46273.
    • Jin, S., MacLean, A. L., Peng, T., Nie, Q. (2018). scEpath: Energy landscape-based inference of transition probabilities and cellular trajectories from single-cell transcriptomic data. Bioinformatics. pp. bty058.
    • Lambert, B., MacLean, A. L., Fletcher, A. G., Combes, A. N., Little, M. H., Byrne, H. M. (2018). Bayesian inference of agent-based models: a tool for studying kidney branching morphogenesis. Journal of Mathematical Biology. Vol. 10 (12), pp. 106.
    • Sharma, P. P., MacLean, A. L., Meinecke, L., Clouthier, D. E., Nie, Q., Schilling, T. F. (2018). Transcriptomics reveals complex kinetics of dorsal-ventral patterning gene expression in the mandibular arch. genesis. pp. e23275.
    • MacLean, A. L., Hong, T., Nie, Q. (2018). Exploring intermediate cell states through the lens of single cells. Curr Opin Sys Biol. Vol. 9, pp. 32-41.
    • Peng, T., Liu, L., MacLean, A. L., Wong, C. W., Zhao, W., Nie, Q. (2017). A mathematical model of mechanotransduction reveals how mechanical memory regulates mesenchymal stem cell fate decisions. BMC Systems Biology. Vol. 11 (1), pp. 55.
    • MacLean, A. L., Smith, M. A., Liepe, J., Sim, A., Khorshed, R., Rashidi, N. M., Scherf, N., Krinner, A., Roeder, I., Lo Celso, C., Stumpf, M. P. (2017). Single Cell Phenotyping Reveals Heterogeneity Among Hematopoietic Stem Cells Following Infection. Stem Cells. Vol. 132, pp. 631.
    • Guo, Y., Nie, Q., MacLean, A. L., Li, Y., Lei, J., Li, S. (2017). Multiscale Modeling of Inflammation-Induced Tumorigenesis Reveals Competing Oncogenic and Oncoprotective Roles for Inflammation. Cancer research. Vol. 77 (22), pp. 6429-6441. PubMed Web Address
    • Vainieri, M. L., Blagborough, A. M., MacLean, A. L., Haltalli, M. L., Ruivo, N., Fletcher, H. A., Stumpf, M. P., Sinden, R. E., Lo Celso, C. (2016). Systematic tracking of altered haematopoiesis during sporozoite-mediated malaria development reveals multiple response points. Open Biology. Vol. 6 (6), pp. 160038.
    • MacLean, A. L., Lo Celso, C., Stumpf, M. P. (2016). Concise Review: Stem Cell Population Biology: Insights from Hematopoiesis. Stem Cells.
    • Crowell, H. L., MacLean, A. L., Stumpf, M. P. (2016). Feedback mechanisms control coexistence in a stem cell model of acute myeloid leukaemia. Journal of Theoretical Biology. Vol. 401, pp. 43-53.
    • MacLean, A. L., Rosen, Z., Byrne, H. M., Harrington, H. A. (2015). Parameter-free methods distinguish Wnt pathway models and guide design of experiments. Proceedings of the National Academy of Sciences of the USA. Vol. 112 (9), pp. 2652-2657.
    • MacLean, A. L., Kirk, P., Stumpf, M. P. (2015). Cellular population dynamics control the robustness of the stem cell niche. Biology Open/Journals of the Company of Biologists.
    • Kirk, P. D., Rolando, D. M., MacLean, A. L., Stumpf, M. P. (2015). Conditional random matrix ensembles and the stability of dynamical systems. New Journal of Physics/IOP Publishing. Vol. 17 (8), pp. 083025.
    • MacLean, A. L., Harrington, H. A., Stumpf, M. P., Hansen, M. (2014). Epithelial-Mesenchymal Transition in Metastatic Cancer Cell Populations Affects Tumor Dormancy in a Simple Mathematical Model. Biomedicines. Vol. 2 (4), pp. 384-402.
    • MacLean, A. L., Filippi, S., Stumpf, M. P. (2014). The ecology in the hematopoietic stem cell niche determines the clinical outcome in chronic myeloid leukemia. Proceedings of the National Academy of Sciences of the USA. Vol. 111 (10), pp. 3882-3888.
    • MacLean, A. L., Lo Celso, C., Stumpf, M. P. (2013). Population dynamics of normal and leukaemia stem cells in the haematopoietic stem cell niche show distinct regimes where leukaemia will be controlled. Journal of the Royal Society Interface.
    • NIH/NSF Career Development Award, NSF CAREER Award , 2021-2022
    • NIH/NSF Career Development Award, R35 MIRA Award, 2021-2022
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