Iain's research group is interested in combining mathematical, statistical, and experimental approaches to learn about the biological world, and how we can interact with it to improve human lives. We often work on questions where "blue skies" biological knowledge can be translated into strategies to address disease and crop production. We're particularly interested in the bioenergetic organelles (mitochondria and chloroplasts) that provide the energy that powers complex life.
One major current focus of the group is EvoConBiO -- an ERC-funded project exploring the evolution and cellular control of mitochondria and chloroplasts, using approaches from stochastic modelling, bioinformatics, and molecular biology.
Some keywords related to our research -- mathematical: stochastic modelling, discrete population processes, inference and model selection, uncertainty quantification, pathway inference; biological: stochastic biology, cell heterogeneity, mitochondria, chloroplasts, mtDNA, cpDNA, evolution, disease progression, bioinformatics, plant systems biology.
The CRIStin profile below is currently being updated.
- (2022). Symmetry and simplicity spontaneously emerge from the algorithmic nature of evolution. Proceedings of the National Academy of Sciences of the United States of America.
- (2022). Sorting of mitochondrial and plastid heteroplasmy in Arabidopsis is extremely rapid and depends on MSH1 activity. Proceedings of the National Academy of Sciences of the United States of America.
- (2022). Optimal strategies in the Fighting Fantasy gaming system: influencing stochastic dynamics by gambling with limited resource. European Journal of Operational Research.
- (2022). Interdisciplinary and Transferable Concepts in Bioinformatics Education: Observations and Approaches From a UK MSc Course. Frontiers in Education.
- (2022). Dynamic Boolean modelling reveals the influence of energy supply on bacterial efflux pump expression. Journal of the Royal Society Interface.
- (2021). Understanding learner behaviour in online courses with Bayesian modelling and time series characterisation. Scientific Reports.
- (2021). Sexually antagonistic evolution of mitochondrial and nuclear linkage. Journal of Evolutionary Biology. 757-766.
- (2021). Network analysis of Arabidopsis mitochondrial dynamics reveals a resolved tradeoff between physical distribution and social connectivity. Cell Systems. 419-431.
- (2021). Avoiding organelle mutational meltdown across eukaryotes with or without a germline bottleneck. PLoS Biology.
- (2021). 2-Deoxy-D-glucose couples mitochondrial DNA replication with mitochondrial fitness and promotes the selection of wild-type over mutant mitochondrial DNA. Nature Communications.
- (2020). S100A4 mRNA-protein relationship uncovered by measurement noise reduction. Journal of Molecular Medicine. 735-749.
- (2020). MtDNA sequence features associated with 'selfish genomes' predict tissue-specific segregation and reversion. Nucleic Acids Research (NAR). 8290-8301.
- (2020). Efficient vasculature investment in tissues can be determined without global information. Journal of the Royal Society Interface.
- (2020). Data-Driven Inference Reveals Distinct and Conserved Dynamic Pathways of Tool Use Emergence across Animal Taxa. iScience.
- (2020). Cell identity and nucleo-mitochondrial genetic context modulate OXPHOS performance and determine somatic heteroplasmy dynamics. Science Advances. 1-13.
- (2019). Varied mechanisms and models for the varying mitochondrial bottleneck. Frontiers in Cell and Developmental Biology. 1-16.
- (2019). Tension and resolution: dynamic, evolving populations of organelle genomes within plant cells. Molecular Plant. 764.
- (2019). Precision identification of high-risk phenotypes and progression pathways in severe malaria without requiring longitudinal data. npj Digital Medicine. 1.
- (2019). Model selection and parameter estimation for root architecture models using likelihood-free inference. Journal of the Royal Society Interface. 1-10.
- (2019). Mitochondrial network state scales mtDNA genetic dynamics. Genetics. 1429-1443.
- (2019). Intracellular Energy Variability Modulates Cellular Decision-Making Capacity. Scientific Reports. 1-12.
- (2019). HyperTraPS: Inferring probabilistic patterns of trait acquisition in evolutionary and disease progression pathways. Cell Systems. 1.
- (2019). Evolving mtDNA populations within cells. Biochemical Society Transactions. 1367.
- (2019). Energetic costs of cellular and therapeutic control of stochastic mitochondrial DNA populations. PLoS Computational Biology. e1007023.
- (2018). Identification of a bet-hedging network motif generating noise in hormone concentrations and germination propensity in Arabidopsis. Journal of the Royal Society Interface. 20180042.
- (2022). Reply to Ocklenburg and Mundorf: The interplay of developmental bias and natural selection. Proceedings of the National Academy of Sciences of the United States of America.
EvoConBiO (ERC StG) -- evolution and control of bioenergetic organelles
CAMRIA (Trond Mohn) -- combatting antimicrobial resistance with interdisciplinary approaches
QUINTUS (UK NERC) -- responses of forest ecosystems to elevated CO2
HyperTraPS (Alan Turing Institute) -- inferring pathways of evolution and disease progression
Iain also supervises researchers on projects funded by the UK BBSRC and Wellcome Trust, working on plant mitochondria, seed germination, and antimicrobial resistance.