Adam MacLean, Postdoctoral Scholar

I have joined the faculty of USC in the Dept. of Quantitative & Computational Biology. Go to group website.

Previously I was a member of the Nie Lab at UCI from September 2016 - December 2018. I have also worked in the Theoretical Systems Biology group at Imperial College London, and at the Mathematical Institute at the University of Oxford.

Go to my ResearchGate, or Google Scholar profile.


My biological research focus is on stem cells, and questions regarding their function, dynamics, and regulation. Individual stem cell decisions (self-renewal, differentiation, death) must be coordinated at many levels, from the molecular and cellular to the tissue/organismal, in order to maintain homeostasis. This is particularly important in high-turnover tissues such as blood, guts, and skin. At multiple scales, complex and noisy nonlinear dynamics emerge. I develop mathematical and computational tools in order to study these systems and illuminate their core mechanisms. These are rooted in dynamical systems theory, inverse problems (Bayesian inference), and applied mathematics.

Application of these tools allows us to address important biological questions. For example, in hematopoietic stem cell biology we study how stem cells maintain the blood system, and how they respond to infections. This requires high spatiotemporal resolution that we can obtain by tracking single stem cells in vivo. We can also study cancer in the context of stem cells, i.e., we consider the ecology of cancer, whereby healthy stem cells respond to and compete with malignant cells that have undergone transformation. We use these models to predict both the mechanisms of cancer progression and the best therapeutic strategies to employ. For the latter, we have found that maintenance of a healthy stem cell population is more important than direct killing of leukemia cells.

Current data (single-cell RNA-seq, barcoding, etc) allow us to probe cellular states in greater detail than ever before. By analysis of mechanistic models in light of these data we distill insight into the tightly regulated transcriptional programs that underlie stem cell phenotype. For example, we can investigate how a balance of cell division, differentiation, and migration allows for both tissue homeostasis and response to an external perturbation (such as a bleed, wound, or infection). I am also fascinated by the transitions between cellular states (such as from quiescent to cycling, or from epithelial to mesenchymal), and am actively developing new models to describe and characterise their dynamics.


In Fall Quarter 2017 I taught Math 5A: Calculus for the Life Sciences at UCI. I have previously helped to teach undergraduate and postgraduate courses at Imperial College London. During my time at UCI, Imperial College, and the University of Oxford, I have (co-)supervised four PhD/DTC students, six Masters/MSc students, and five undergraduate students.


I have held research positions as a Postdoctoral Research Associate in the Theoretical Systems Biology Group at Imperial College London (2015-2016) and in the Mathematical Institute at the University of Oxford (2014). I completed my PhD in the Theoretical Systems Biology Group: my thesis is entitled Modelling haematopoietic stem cells in their niche. I have also completed a BSc in Mathematical Physics at the University of Edinburgh (graduating 2009 with first class honours) and an MSc in Bioinformatics and Theoretical Systems Biology at Imperial College London (graduating 2010 with distinction).

Outside of research I am passionate about writing, communication, and combinations thereof. I have helped to curate events including the Summer Science Exhibition and Imagining the Future of Medicine. I have co-edited a short fiction column at Londonist.



16. S Wang, AL MacLean, Q Nie, (2018) Low-rank similarity matrix optimization identifies subpopulation structure and orders single cells in pseudotime. Submitted, bioRvix, doi:10.1101/168922.

15. AL MacLean*, T Hong*, Q Nie, (2018) Exploring intermediate cell states through the lens of single cells. Curr Opin Sys Biol, doi:10.1016/j.coisb.2018.02.009.

14. S Jin, AL MacLean, T Peng, Q Nie, (2018) Energy landscape-based inference of transition probabilities and cellular trajectories from single-cell transcriptomic data. Bioinformatics, doi:10.1093/bioinformatics/bty058.

13. Ben Lambert*, AL MacLean*, AG Fletcher, AN Coombes, MH Little, HM Byrne, (2018) Bayesian inference of agent-based models: a tool for studying kidney branching morphogenesis. J Math Biol, doi:10.1007/s00285-018-1208-z.


12. Y Guo, Q Nie, AL MacLean, Y Li, J Lei, and S Li, (2017) An agent-based model reveals evolutionary dynamics of inflammation-induced cancer. Cancer Research doi:10.1158/0008-5472.CAN-17-1662.

11. AL MacLean*, MA Smith*, J Liepe, A Sim, R Khorshed, NM Rashidi, N Scherf, A Krinner, I Roeder, C Lo Celso, MPH Stumpf, (2017) Single Cell Phenotyping Reveals Heterogeneity among Haematopoietic Stem Cells Following Infection. Stem Cells, doi:10.1002/stem2692.

10. T Peng*, L Liu*, AL MacLean, CW Wong, W Zhao, Q Nie, (2017) A mathematical model of mechanotransduction reveals how mechanical memory regulates mesenchymal stem cell fate decisions. BMC Sys Bio, doi:10.1186/s12918-017-0429-x.

9. AL MacLean, C Lo Celso, MPH Stumpf, (2017) Stem Cell Population Biology: Insights from Haematopoiesis. Stem Cells, doi:10.1002/stem.2508.

2013 - 2016

8. M Vainieri, A Blagborough, AL MacLean, N Ruivo, H Fletcher, MPH Stumpf, R Sinden, C Lo Celso, (2016) Systematic tracking of altered haematopoiesis during sporozoite-mediated malaria development reveals multiple response points. Open Biology, doi:10.1098/rsob.160038.

7. HL Crowell*, AL MacLean*, MPH Stumpf, (2016) Feedback mechanisms control coexistence in a stem cell model of acute myeloid leukaemia. J Theor Biol, doi:10.1016/j.jtbi.2016.04.002.

6. AL MacLean*, P Kirk*, MPH Stumpf, (2015) Cellular Population Dynamics Control the Robustness of the Stem Cell Niche. Biol Open, doi:10.1242/bio.013714.

5. P Kirk*, DMY Rolando*, AL MacLean, MPH Stumpf, (2015) Conditional Random Matrix Ensembles and the Stability of Dynamical Systems. New J Phys, 17(8), doi:10.1088/1367-2630/17/8/083025.

4. AL MacLean, Z Rosen, HM Byrne, HA Harrington, (2015) Parameter-free methods distinguish Wnt pathway models and guide design of experiments. Proc Natl Acad Sci USA, 112(9), pp. 2652-2657. doi:10.1073/pnas.1416655112.

3. AL MacLean, HA Harrington, MPH Stumpf, MDH Hansen, (2014) Epithelial-mesenchymal transition in metastases affects tumor dormancy in a simple mathematical model. Biomedicines, 2(4) pp. 384-402. doi:10.3390/biomedicines2040384.

2. AL MacLean*, S Filippi*, MPH Stumpf, (2014) Ecology in the hematopoietic stem cell niche determines the clinical outcome in chronic myeloid leukemia. Proc Natl Acad Sci USA, 111(10) pp. 3882-88. doi: 10.1073/pnas.1317072111.

1. AL MacLean, C Lo Celso, MPH Stumpf, (2013) Population dynamics of normal and leukaemia stem cells in the haematopoietic stem cell niche show distinct regimes where leukaemia will be controlled. J R Soc Interface, 2013. doi:10.1098/rsif.2012.0968.

Book Chapter

Mathematical and Statistical Techniques for Systems Medicine: The Wnt Signaling Pathway as a Case Study
AL MacLean, HA Harrington, MPH Stumpf, HM Byrne
in Systems Medicine: Methods in Molecular Biology; 2016, Springer.

Oral Communications & Conferences

  • "The propagation of uncertainty through stem cell population data" (Invited Talk)
    Stem Cell Math Lab 2016: Systems Medicine of Leukemia
    Hamburg, Germany, June 2016.
  • "Parameter-free methods for systems biology to distinguish Wnt models and guide design of experiments" (Invited Talk)
    Mathematics of Reaction Networks Group, Dept. of Mathematical Sciences
    University of Copenhagen, Copenhagen, Denmark, May 2016.
  • "Single Cell Phenotyping Reveals Heterogeneity among Stem Cells Following Infection" (Poster)
    The Stem Cell Niche: Copenhagen Biosciences Conferences
    Copenhagen, Denmark, May 2016.
  • "Haematopoietic Stem Cell Niche Dynamics: leukaemia prognosis and life histories" (Invited Talk)
    Cancer Bioinformatics Seminar Series, Wellcome Trust Centre for Human Genetics
    University of Oxford, Oxford, UK, April 2016.
  • "Hematopoietic Stem Cell Niche Dynamics control Competition, CML Prognosis, and the Robustness of the Niche" (Poster)
    Cancer as an Evolving and Systemic Disease (Nature Conferences)
    Memorial Sloan Kettering Cancer Center, New York, USA, March 2016.
  • "Parameter-free methods for systems biology distinguish Wnt pathway models and guide design of experiments" (Talk)
    MASAMB (Mathematical and Statistical Aspects of Molecular Biology)
    University of Helsinki, Finland, April 2015.
  • "Model selection and comparison of chronic myeloid leukemia" (Invited Talk)
    Meeting on Parameter Inference and Identifiability
    University of Oxford, UK, January 2014.
  • "The effects of hematopoietic stem cell niche dynamics on chronic myeloid leukemia" (Poster)
    Systems Biology of Stem Cells
    University of California Irvine, USA, June 2013.
  • "Dynamics of haematopoiesis: strategies for eradicating leukaemia from the niche" (Poster)
    International Congress on Stem Cells and Tissue Formation
    Dresden, Germany, July 2012.
  • "Population dynamics of normal and leukaemia stem cells in the haematopoietic stem cell niche" (Talk)
    MASAMB (Mathematical and Statistical Aspects of Molecular Biology)
    Berlin, Germany, April 2012.
  • "Population dynamics of healthy and leukaemia stem cells in the haematopoietic stem cell niche" (Poster)
    JST/BBSRC Molecular Imaging and Systems Biology
    Tokyo, Japan, January 2012.
  • "Modelling the haematopoietic stem cell niche with simple dynamical models of competition" (Poster)
    ENFIN Enabling Systems Biology
    UCL, London, UK, April 2011.