I. Johnston

发表

Global Topological Order Emerges through Local Mechanical Control of Cell Divisions in the Arabidopsis Shoot Apical Meristem

G. Bassel, Matthew D B Jackson, Salva Duran-Nebreda, 2019, Cell systems.

What is the function of mitochondrial networks? A theoretical assessment of hypotheses and proposal for future research

Iain G. Johnston, I. Johnston, N. Jones, 2015, BioEssays : news and reviews in molecular, cellular and developmental biology.

Evolutionary Inference across Eukaryotes Identifies Specific Pressures Favoring Mitochondrial Gene Retention.

I. Johnston, Ben P. Williams, 2016, Cell systems.

Evolutionary Inference across Eukaryotes Identifies Specific Pressures Favoring Mitochondrial Gene Retention.

Iain G. Johnston, I. Johnston, Ben P. Williams, 2016, Cell systems.

The effect of scale-free topology on the robustness and evolvability of genetic regulatory networks.

Iain G. Johnston, Sam F. Greenbury, J. Doye, 2010, Journal of theoretical biology.

The self-assembly of DNA Holliday junctions studied with a minimal model.

Iain G. Johnston, J. Doye, A. Louis, 2008, The Journal of chemical physics.

Modelling the self-assembly of virus capsids

Iain G. Johnston, J. Doye, A. Louis, 2009, Journal of physics. Condensed matter : an Institute of Physics journal.

Self-assembly, modularity, and physical complexity.

J. Doye, S. Ahnert, T. Fink, 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.

The State of Vaccine Confidence 2016: Global Insights Through a 67-Country Survey

Iain G. Johnston, A. Cook, H. Larson, 2016, EBioMedicine.

The Essential Genome of Escherichia coli K-12

Iain G. Johnston, I. Henderson, A. Cunningham, 2017, mBio.

The chaos within: exploring noise in cellular biology

Iain G. Johnston, I. Johnston, 2012 .

Intracellular Energy Variability Modulates Cellular Decision-Making Capacity

I. Johnston, S. Jabbari, Ryan Kerr, 2019, Scientific Reports.

Intracellular Energy Variability Modulates Cellular Decision-Making Capacity

Iain G. Johnston, I. Johnston, S. Jabbari, 2019, Scientific Reports.

Identification of a bet-hedging network motif generating noise in hormone concentrations and germination propensity in Arabidopsis

Iain G. Johnston, G. Bassel, I. Johnston, 2018, Journal of The Royal Society Interface.

Variability in seeds: biological, ecological, and agricultural implications

Iain G. Johnston, G. Bassel, I. Johnston, 2016, Journal of experimental botany.

Energetic costs of cellular and therapeutic control of stochastic mtDNA populations

Iain G. Johnston, M. Minczuk, I. Johnston, 2017, bioRxiv.

Mitochondrial DNA density homeostasis accounts for a threshold effect in a cybrid model of a human mitochondrial disease

Iain G. Johnston, I. Johnston, N. Jones, 2017, The Biochemical journal.

Mitochondrial DNA Density Homeostasis Accounts for the Threshold Effect in Human Mitochondrial Disease

I. Johnston, N. Jones, J. Aryaman, 2016, bioRxiv.

Stochastic modelling, Bayesian inference, and new in vivo measurements elucidate the debated mtDNA bottleneck mechanism

Iain G. Johnston, Joerg P Burgstaller, Vitezslav Havlicek, 2015, eLife.

Global Topological Order Emerges through Local Mechanical Control of Cell Divisions in the Arabidopsis Shoot Apical Meristem

Iain G. Johnston, G. Bassel, Matthew D B Jackson, 2019, Cell systems.

Mitochondrial Heterogeneity

Iain G. Johnston, I. Johnston, N. Jones, 2018, Front. Genet..

Mitochondrial network fragmentation modulates mutant mtDNA accumulation independently of absolute fission-fusion rates

Iain G. Johnston, I. Johnston, N. Jones, 2018 .

Stochastic Models for Evolving Cellular Populations of Mitochondria: Disease, Development, and Ageing

Iain G. Johnston, I. Johnston, N. Jones, 2017 .

A tractable genotype-phenotype map for the self-assembly of protein quaternary structure

S. Ahnert, A. Louis, I. Johnston, 2013, 1311.0399.

Varied Mechanisms and Models for the Varying Mitochondrial Bottleneck

Iain G. Johnston, I. Johnston, 2019, Front. Cell Dev. Biol..

Evolving mtDNA populations within cells

Iain G. Johnston, I. Johnston, J. Burgstaller, 2019, Biochemical Society transactions.

Evolution of cell-to-cell variability in stochastic, controlled, heteroplasmic mtDNA populations

Iain G. Johnston, I. Johnston, N. Jones, 2016, bioRxiv.

Evolution of Cell-to-Cell Variability in Stochastic, Controlled, Heteroplasmic mtDNA Populations.

Iain G. Johnston, I. Johnston, N. Jones, 2016, American journal of human genetics.

Programme - Day 1

Iain G. Johnston, Sam F. Greenbury, Marjon G. J. de Vos, 2021 .

Regulation of Mother-to-Offspring Transmission of mtDNA Heteroplasmy

Iain G. Johnston, I. Johnston, N. Jones, 2019, Cell metabolism.

Modulating mitochondrial quality in disease transmission: towards enabling mitochondrial DNA disease carriers to have healthy children

Iain G. Johnston, I. Johnston, D. Wells, 2016, Biochemical Society transactions.

Mitochondrial heterogeneity, metabolic scaling and cell death

Iain G. Johnston, I. Johnston, N. Jones, 2017, BioEssays : news and reviews in molecular, cellular and developmental biology.

HyperHMM: efficient inference of evolutionary and progressive dynamics on hypercubic transition graphs

Iain G. Johnston, I. Johnston, Marcus T. Moen, 2022, bioRxiv.

Pulsing of Membrane Potential in Individual Mitochondria: A Stress-Induced Mechanism to Regulate Respiratory Bioenergetics in Arabidopsis[W]

M. Fricker, I. Johnston, N. Jones, 2012, Plant Cell.

Tension and Resolution: Dynamic, Evolving Populations of Organelle Genomes within Plant Cells.

Iain G. Johnston, I. Johnston, 2019, Molecular plant.

S100A4 mRNA-protein relationship uncovered by measurement noise reduction

Iain G. Johnston, I. Johnston, T. Nussbaumer, 2020, Journal of Molecular Medicine.

Precision identification of high-risk phenotypes and progression pathways in severe malaria without requiring longitudinal data

D. Kwiatkowski, M. Jallow, Mauricio Barahona, 2019, npj Digital Medicine.

Precision identification and prediction of high mortality phenotypes and disease progression pathways in severe malaria without requiring longitudinal data

D. Kwiatkowski, M. Jallow, I. Johnston, 2018, bioRxiv.

mtDNA diversity in human populations highlights the merit of haplotype matching in gene therapies

I. Johnston, E. C. Røyrvik, J. Burgstaller, 2016, bioRxiv.

Mitochondrial DNA disease and developmental implications for reproductive strategies

Iain G. Johnston, I. Johnston, J. Poulton, 2014, Molecular human reproduction.

MtDNA segregation in heteroplasmic tissues is common in vivo and modulated by haplotype differences and developmental stage.

Iain G. Johnston, A. Futschik, J. Albrechtová, 2014, Cell reports.

Monitoring Intracellular Oxygen Concentration: Implications for Hypoxia Studies and Real-Time Oxygen Monitoring.

I. Johnston, K. Morten, Luned M. Badder, 2016, Advances in experimental medicine and biology.

Evolutionary inference across eukaryotes identifies specific pressures favoring mtDNA gene retention

Iain G. Johnston, I. Johnston, Ben P. Williams, 2016, bioRxiv.

Forecasted trends in vaccination coverage and correlations with socioeconomic factors: a global time-series analysis over 30 years.

Iain G. Johnston, H. Larson, I. Johnston, 2016, The Lancet. Global health.

Mitochondrial network structure controls cell-to-cell mtDNA variability generated by cell divisions

Iain G. Johnston, I. Johnston, Robert C. Glastad, 2022, bioRxiv.

MtDNA sequence features associated with ‘selfish genomes’ predict tissue-specific segregation and reversion

Iain G. Johnston, I. Johnston, E. C. Røyrvik, 2020, Nucleic acids research.

Cell identity and nucleo-mitochondrial genetic context modulate OXPHOS performance and determine somatic heteroplasmy dynamics

Iain G. Johnston, S. Priori, I. Johnston, 2020, Science Advances.

Large-scale genetic analysis reveals mammalian mtDNA heteroplasmy dynamics and variance increase through lifetimes and generations

Iain G. Johnston, J. Piálek, T. Rülicke, 2018, Nature Communications.

Sorting of mitochondrial and plastid heteroplasmy in Arabidopsis is extremely rapid and depends on MSH1 activity

Iain G. Johnston, Daniel B. Sloan, I. Johnston, 2022, bioRxiv.

Avoiding misleading estimates using mtDNA heteroplasmy statistics to study bottleneck size and selection

Iain G. Johnston, Daniel B. Sloan, I. Johnston, 2022, bioRxiv.

Exchange on dynamic encounter networks allows plant mitochondria to collect complete sets of mitochondrial DNA products despite their incomplete genomes

Iain G. Johnston, I. Johnston, Konstantinos Giannakis, 2022, Quantitative Plant Biology.

Cell identity and nucleo-mitochondrial genetic context modulate OXPHOS performance and determine somatic heteroplasmy dynamics.

S. Priori, I. Johnston, N. Jones, 2020, Science advances.

Evolutionary inference across eukaryotes identifies universal features shaping organelle gene retention.

Iain G. Johnston, I. Johnston, E. C. Røyrvik, 2022, Cell systems.

The ‘mitoflash’ probe cpYFP does not respond to superoxide

M. Fricker, M. Duchen, H. Forman, 2014, Nature.

Review of the safety and efficacy of polar body transfer to avoid mitochondrial disease Addendum to ‘ Third scientific review of the safety and efficacy of methods to avoid mitochondrial disease through assisted conception : 2014 update

I. Johnston, Mitochondrial Genetics, 2014 .

Dynamics of organelle DNA segregation in Arabidopsis development and reproduction revealed with tissue-specific heteroplasmy profiling and stochastic modelling

Daniel B. Sloan, I. Johnston, A. Broz, 2022, bioRxiv.

Encounter networks from collective mitochondrial dynamics support the emergence of effective mtDNA genomes in plant cells

Iain G. Johnston, I. Johnston, Konstantinos Giannakis, 2021, bioRxiv.

Avoiding organelle mutational meltdown across eukaryotes with or without a germline bottleneck

I. Johnston, E. C. Røyrvik, Konstantinos Giannakis, 2021, PLoS biology.

FRIENDLY Regulates Mitochondrial Distribution, Fusion, and Quality Control in Arabidopsis1[W][OPEN]

Iain G. Johnston, I. Johnston, N. Jones, 2014, Plant Physiology.

Altered collective mitochondrial dynamics in the Arabidopsis msh1 mutant compromising organelle DNA maintenance

Iain G. Johnston, D. Gibbs, I. Johnston, 2021, bioRxiv.

Symmetry and simplicity spontaneously emerge from the algorithmic nature of evolution

Iain G. Johnston, Chico Q. Camargo, Sam F. Greenbury, 2021, bioRxiv.

Data science approaches provide a roadmap to understanding the role of abscisic acid in defence

Iain G. Johnston, I. Johnston, Estrella Luna, 2022, bioRxiv.

Mitochondrial Network Fragmentation Modulates Mutant mtDNA Accumulation Independently of Absolute Fission-Fusion Rates.

I. Johnston, N. Jones, J. Aryaman, 2018, Genetics.

Model selection and parameter estimation for root architecture models using likelihood-free inference

Iain G. Johnston, Clare Ziegler, Rosemary J. Dyson, 2019, Journal of the Royal Society Interface.

Mitochondrial Variability as a Source of Extrinsic Cellular Noise

Iain G. Johnston, Nick S. Jones, Tariq Enver, 2011, PLoS Comput. Biol..

Energetic costs of cellular and therapeutic control of stochastic mitochondrial DNA populations

Iain G. Johnston, Hanne Hoitzing, Nick S Jones, 2019, PLoS Comput. Biol..

Toward Precision Healthcare: Context and Mathematical Challenges

Iain G. Johnston, Nick Jones, Caroline Colijn, 2017, Front. Physiol..

Changing socioeconomic determinants of childhood vaccines: a global analysis over three decades

H. Larson, I. Johnston, N. Jones, 2015 .

Phenotypic landscape inference reveals multiple evolutionary paths to C4 photosynthesis

Iain G. Johnston, I. Johnston, J. Hibberd, 2013, eLife.

A tractable genotype–phenotype map modelling the self-assembly of protein quaternary structure

Iain G. Johnston, Sebastian E. Ahnert, Ard A. Louis, 2014, Journal of The Royal Society Interface.

What is quantitative plant biology?

Iain G. Johnston, Dorota Kwiatkowska, Olivier Hamant, 2021, Quantitative Plant Biology.

Temperature variability is integrated by a spatially embedded decision-making center to break dormancy in Arabidopsis seeds

Iain G. Johnston, Eiji Nambara, G. Bassel, 2017, Proceedings of the National Academy of Sciences.

A novel quantitative assay of mitophagy: Combining high content fluorescence microscopy and mitochondrial DNA load to quantify mitophagy and identify novel pharmacological tools against pathogenic heteroplasmic mtDNA.

Iain G. Johnston, I. Johnston, C. Sue, 2015, Pharmacological research.

Epistasis can lead to fragmented neutral spaces and contingency in evolution

Ard A Louis, Iain G Johnston, Steffen Schaper, 2011, Proceedings of the Royal Society B: Biological Sciences.

Closed-form stochastic solutions for non-equilibrium dynamics and inheritance of cellular components over many cell divisions

Iain G. Johnston, Nick S. Jones, I. Johnston, 2015, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences.

Paternal leakage of organelles can improve adaptation to changing environments

Iain G. Johnston, I. Johnston, A. Radzvilavicius, 2020, bioRxiv.

2-Deoxy-D-glucose couples mitochondrial DNA replication with mitochondrial fitness and promotes the selection of wild-type over mutant mitochondrial DNA

Iain G. Johnston, Robert W. Taylor, I. Johnston, 2021, Nature Communications.

Cellular and environmental dynamics influence species-specific extents of organelle gene retention

Iain G. Johnston, J. Nordbotten, I. Johnston, 2022, bioRxiv.

Universal features shaping organelle gene retention

Iain G. Johnston, I. Johnston, E. C. Røyrvik, 2021, bioRxiv.

Data-Driven Inference Reveals Distinct and Conserved Dynamic Pathways of Tool Use Emergence across Animal Taxa

Iain G. Johnston, Ellen C. Røyrvik, I. Johnston, 2020, iScience.

Mitochondrial DNA Density Homeostasis Accounts for the Threshold Effect in Human Mitochondrial Disease

I. Johnston, N. Jones, J. Aryaman, 2016, bioRxiv.

Dynamic Boolean modelling reveals the influence of energy supply on bacterial efflux pump expression

Iain G. Johnston, I. Johnston, S. Jabbari, 2021, bioRxiv.

Mitochondrial network state scales mtDNA genetic dynamics

Iain G. Johnston, I. Johnston, N. Jones, 2019 .

Large-scale genetic analysis reveals mammalian mtDNA heteroplasmy dynamics and variance increase through lifetimes and generations

J. Piálek, T. Rülicke, I. Johnston, 2018, Nature Communications.

Evolutionary dynamics in a simple model of self-assembly.

Sebastian E Ahnert, Jonathan P K Doye, Ard A Louis, 2011, Physical review. E, Statistical, nonlinear, and soft matter physics.

Metabolic role of the hepatic valine/3-hydroxyisobutyrate (3-HIB) pathway in fatty liver disease

Iain G. Johnston, I. Johnston, S. Dankel, 2023, EBioMedicine.

Understanding learner behaviour in online courses with Bayesian modelling and time series characterisation

Mauricio Barahona, I. Johnston, S. Yaliraki, 2021, Scientific Reports.

Efficient vasculature investment in tissues can be determined without global information

Iain G. Johnston, Salva Duran-Nebreda, George W. Bassel, 2020, Journal of the Royal Society Interface.

Inferring high-dimensional pathways of trait acquisition in evolution and disease

Iain G. Johnston, Mauricio Barahona, Sam F. Greenbury, 2018, bioRxiv.

using a stable isotope-mass spectrometric technique Measurement of mitochondrial DNA synthesis in vivo

Iain G. Johnston, D. Matthews, M. Kjaer, 2015 .

Reply to Ocklenburg and Mundorf: The interplay of developmental bias and natural selection

Chico Q. Camargo, J. Doye, S. Ahnert, 2022, Proceedings of the National Academy of Sciences of the United States of America.

Sexually antagonistic evolution of mitochondrial and nuclear linkage

Iain G. Johnston, I. Johnston, M. Hall, 2021, bioRxiv.

Quantification and uncertainty of root growth stimulation by elevated CO2 in mature temperate deciduous forest

Iain G. Johnston, I. Johnston, R. Dyson, 2021, bioRxiv.

Network analysis of Arabidopsis mitochondrial dynamics reveals a resolved tradeoff between physical distribution and social connectivity

Iain G. Johnston, G. Bassel, D. Gibbs, 2021, Cell systems.

Efficient parametric inference for stochastic biological systems with measured variability

Iain G Johnston, I. Johnston, 2014, Statistical applications in genetics and molecular biology.

Mitochondrial Network State Scales mtDNA Genetic Dynamics.

I. Johnston, N. Jones, J. Aryaman, 2018, Genetics.

Organelle bottlenecks facilitate evolvability by traversing heteroplasmic fitness valleys

Iain G. Johnston, I. Johnston, A. Radzvilavicius, 2021, bioRxiv.

Ecological predictors of organelle genome evolution: Phylogenetic correlations with taxonomically broad, sparse, unsystematized data

I. Johnston, Konstantinos Giannakis, Luke Richards, 2023, bioRxiv.