Iain Johnston's picture

Iain Johnston

Professor, Department of Mathematics and Associate Group Leader, Computational Biology Unit
  • E-mailiain.johnston@uib.no
  • Visitor Address
    Allégaten 41
    5007 Bergen
  • Postal Address
    Postboks 7803
    5020 Bergen

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.

You can read more at the research group website, and find non-technical summaries of research papers here.

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. 

Iain's publications can be found on Google Scholar here or ORCID here .

The CRIStin profile below is currently being updated.

Academic article
  • Show author(s) (2024). Nucleoside supplements as treatments for mitochondrial DNA depletion syndrome. Frontiers in Cell and Developmental Biology.
  • Show author(s) (2023). Stromule Geometry Allows Optimal Spatial Regulation of Organelle Interactions in the Quasi-2D Cytoplasm. Plant and Cell Physiology. 618-630.
  • Show author(s) (2023). Stochastic organelle genome segregation through Arabidopsis development and reproduction. New Phytologist.
  • Show author(s) (2023). Mitochondrial network structure controls cell-to-cell mtDNA variability generated by cell divisions. PLoS Computational Biology.
  • Show author(s) (2023). Metabolic role of the hepatic valine/3-hydroxyisobutyrate (3-HIB) pathway in fatty liver disease. EBioMedicine. 18 pages.
  • Show author(s) (2023). Data science approaches provide a roadmap to understanding the role of abscisic acid in defence. Quantitative Plant Biology.
  • Show author(s) (2023). Cellular and environmental dynamics influence species-specific extents of organelle gene retention. Proceedings of the Royal Society of London. Biological Sciences.
  • Show author(s) (2023). Avoiding misleading estimates using mtDNA heteroplasmy statistics to study bottleneck size and selection. G3: Genes, Genomes, Genetics.
  • Show author(s) (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.
  • Show author(s) (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.
  • Show author(s) (2022). Quantification and uncertainty of root growth stimulation by elevated CO<inf>2</inf> in a mature temperate deciduous forest. Science of the Total Environment.
  • Show author(s) (2022). Organelle bottlenecks facilitate evolvability by traversing heteroplasmic fitness valleys. Frontiers in Genetics.
  • Show author(s) (2022). Optimal strategies in the Fighting Fantasy gaming system: influencing stochastic dynamics by gambling with limited resource. European Journal of Operational Research. 1272-1281.
  • Show author(s) (2022). Interdisciplinary and Transferable Concepts in Bioinformatics Education: Observations and Approaches From a UK MSc Course. Frontiers in Education.
  • Show author(s) (2022). HyperHMM: efficient inference of evolutionary and progressive dynamics on hypercubic transition graphs. Bioinformatics.
  • Show author(s) (2022). Exchange on dynamic encounter networks allows plant mitochondria to collect complete sets of mitochondrial DNA products despite their incomplete genomes. Quantitative Plant Biology.
  • Show author(s) (2022). Evolutionary inference across eukaryotes identifies universal features shaping organelle gene retention. Cell Systems. 874-884.e5.
  • Show author(s) (2022). Dynamic Boolean modelling reveals the influence of energy supply on bacterial efflux pump expression. Journal of the Royal Society Interface. 1-14.
  • Show author(s) (2022). Altered collective mitochondrial dynamics in the Arabidopsis msh1 mutant compromising organelle DNA maintenance. Journal of Experimental Botany. 5428-5439.
  • Show author(s) (2021). Understanding learner behaviour in online courses with Bayesian modelling and time series characterisation. Scientific Reports.
  • Show author(s) (2021). Sexually antagonistic evolution of mitochondrial and nuclear linkage. Journal of Evolutionary Biology. 757-766.
  • Show author(s) (2021). Network analysis of Arabidopsis mitochondrial dynamics reveals a resolved tradeoff between physical distribution and social connectivity. Cell Systems. 419-431.
  • Show author(s) (2021). Avoiding organelle mutational meltdown across eukaryotes with or without a germline bottleneck. PLoS Biology.
  • Show author(s) (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.
  • Show author(s) (2020). S100A4 mRNA-protein relationship uncovered by measurement noise reduction. Journal of Molecular Medicine. 735-749.
  • Show author(s) (2020). MtDNA sequence features associated with 'selfish genomes' predict tissue-specific segregation and reversion. Nucleic Acids Research (NAR). 8290-8301.
  • Show author(s) (2020). Efficient vasculature investment in tissues can be determined without global information. Journal of the Royal Society Interface.
  • Show author(s) (2020). Data-Driven Inference Reveals Distinct and Conserved Dynamic Pathways of Tool Use Emergence across Animal Taxa. iScience.
  • Show author(s) (2020). Cell identity and nucleo-mitochondrial genetic context modulate OXPHOS performance and determine somatic heteroplasmy dynamics. Science Advances. 1-13.
  • Show author(s) (2019). Varied mechanisms and models for the varying mitochondrial bottleneck. Frontiers in Cell and Developmental Biology. 1-16.
  • Show author(s) (2019). Tension and resolution: dynamic, evolving populations of organelle genomes within plant cells. Molecular Plant. 764.
  • Show author(s) (2019). Precision identification of high-risk phenotypes and progression pathways in severe malaria without requiring longitudinal data. npj Digital Medicine. 1.
  • Show author(s) (2019). Model selection and parameter estimation for root architecture models using likelihood-free inference. Journal of the Royal Society Interface. 1-10.
  • Show author(s) (2019). Mitochondrial network state scales mtDNA genetic dynamics. Genetics. 1429-1443.
  • Show author(s) (2019). Intracellular Energy Variability Modulates Cellular Decision-Making Capacity. Scientific Reports. 1-12.
  • Show author(s) (2019). HyperTraPS: Inferring probabilistic patterns of trait acquisition in evolutionary and disease progression pathways. Cell Systems. 1.
  • Show author(s) (2019). Evolving mtDNA populations within cells. Biochemical Society Transactions. 1367.
  • Show author(s) (2019). Energetic costs of cellular and therapeutic control of stochastic mitochondrial DNA populations. PLoS Computational Biology. e1007023.
  • Show author(s) (2019). Regulation of Mother-to-Offspring Transmission of mtDNA Heteroplasmy. Cell Metabolism.
  • Show author(s) (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.
Letter to the editor
  • Show author(s) (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.
  • Show author(s) (2023). Stochastic and Deterministic Computation in the regulation of Decision – Making Genetic circuits by Energy Availability.
  • Show author(s) (2023). Population Dynamics in Response to Environmental Stimuli.
Academic literature review
  • Show author(s) (2023). Collective mitochondrial dynamics resolve conflicting cellular tensions: From plants to general principles. Seminars in Cell and Developmental Biology. 253-265.
  • Show author(s) (2021). What is quantitative plant biology? Quantitative Plant Biology.

More information in national current research information system (CRIStin)

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.