I am a BBSRC-funded research fellow based in the Theoretical Systems Biology group at Imperial College. I use a variety of mathematical and statistical approaches to study the structure and regulation of biological networks. My current research focuses on developing methods to analyse single-cell transcriptomic data, and approaches to assess uncertainty in mathematical models of biological systems.
et al., 2020, Single cell analyses and machine learning define hematopoietic progenitor and HSC-like cells derived from human PSCs, Blood, Vol:136, ISSN:0006-4971, Pages:2893-2904
Babtie AC, 2019, Modelling heterogeneous intracellular networks at the cellular scale, Current Opinion in Systems Biology, Vol:16, ISSN:2452-3100, Pages:10-16
Chan TE, Stumpf MPH, Babtie AC, 2019, Gene Regulatory Networks from Single Cell Data for Exploring Cell Fate Decisions., Methods Mol Biol, Vol:1975, Pages:211-238
Babtie AC, Chan TE, Stumpf MPH, 2017, Learning regulatory models for cell development from single cell transcriptomic data, Current Opinion in Systems Biology, Vol:5, ISSN:2452-3100, Pages:72-81
Chan TE, Stumpf MPH, Babtie AC, 2017, Gene regulatory network inference from sngle-cell data using multivariate information measures, Cell Systems, Vol:5, ISSN:2405-4712, Pages:251-267.e3