Author

I. G. Johnston

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Cell Biology· 1 Evolutionary Biology· 1 Pathology· 1 Plant Biology· 1

Signature Assays, Organisms & Methods

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Research Focus:chromatin & epigenetic regulation· 3 Assay:DNA methylation· 2 Research Focus:gene regulatory network inference· 2 Approach:machine learning (classical)· 2 Approach:statistical model· 2 Assay:whole-genome sequencing· 2 Organism:Arabidopsis· 1 Approach:Bayesian inference· 1

Frequent Co-Authors

N. S. Jones· 2 shared A. K. Broz· 1 shared A. Keene· 1 shared C. Bowles· 1 shared C. Casals-Pascual· 1 shared D. B. Sloan· 1 shared D. Kwiatkowski· 1 shared E. C. Royrvik· 1 shared

Activity by Year

2018-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 10 mutual co-author links

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2 shared papersCell Biology

N. S. Jones

Mutual co-authors in cluster

Author profile →

4 papers

Recent·Most cited

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

A. K. Broz, A. Keene, M. Fernandes Gyorfy, M. Hodous, I. G. Johnston, D. B. Sloan

This study tracks the inheritance of mitochondrial and plastid mutations in Arabidopsis, finding rapid heteroplasmic sorting and a role for MSH1 in accelerating this process.

bioRxiv · Mar 28, 2022 · PreprintPlant Biology

Universal features shaping organelle gene retention

K. Giannakis, S. J. Arrowsmith, L. Richards, S. Gasparini, J. M. Chustecki, E. C. Royrvik, I. G. Johnston

The paper identifies universal features shaping organelle gene retention using over 15k oDNA sequences and whole genome data, revealing hydrophobicity and energetic centrality as key predictors.

bioRxiv · Oct 27, 2021 · PreprintEvolutionary Biology

Mitochondrial network state scales mtDNA genetic dynamics

J. Aryaman, C. Bowles, N. S. Jones, I. G. Johnston

This study develops a theoretical framework linking mitochondrial network structure to genetic dynamics, showing that network state influences heteroplasmy variance and mutation clearance.

bioRxiv · Jul 3, 2019Cell Biology

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

T. Hoffmann, I. G. Johnston, S. Greenbury, O. Cominetti, M. Jallow, D. Kwiatkowski, M. Barahona, N. S. Jones, C. Casals-Pascual

bioRxiv · Sep 24, 2018Pathology