Author

Connor Reynolds

Earlham InstituteORCID 0000-0002-8923-9557Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Organism:Arabidopsis· 2 Research Focus:differential expression· 2 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Research Focus:gene regulatory network inference· 1 Assay:imaging· 1 Approach:machine learning (classical)· 1 Assay:metagenomics· 1

Frequent Co-Authors

Anthony J W HalliD· 2 shared Antony N. DoddiD· 1 shared Dora Cano Ramirez· 1 shared Ehsan KhajoueiiD· 1 shared Enrico Sandro ColizziiD· 1 shared Fiona Jingxuan Zhang· 1 shared Hannah ReesiD· 1 shared Hiroshi KudohiD· 1 shared

Activity by Year

2025-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 25 mutual co-author links

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2 shared papersPlant Biology

Anthony J W HallORCID

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2 papers

Recent·Most cited

Regulatory architecture tunes gene expression noise in the plant heat shock response

Rituparna Goswami, Dora Cano Ramirez, Katie Abley, Mana Afsharinafar, Connor Reynolds, Jiayi Zeng, Marcel Bhattarai, Fiona Jingxuan Zhang, Sandra Cortijo, Anthony J W Hall, Enrico Sandro Colizzi, James C W Locke

This study shows that the plant heat shock regulatory network controls both the magnitude and distribution of stress-responsive gene expression across cells.

bioRxiv · Oct 25, 2026 · PreprintPlant Biology

Machine learning models reveal environmental and genetic factors associated with the plant circadian clock

Connor Reynolds, Joshua Colmer, Hannah Rees, Ehsan Khajouei, Rachel Rusholme‐Pilcher, Hiroshi Kudoh, Antony N. Dodd, Anthony J W Hall

This study develops ChronoGauge, a machine learning model that estimates plant circadian time from transcriptomic data, enabling analysis of environmental and genetic factors affecting the circadian clock.

Nature Communications · Aug 5, 2025Peer-reviewedPlant Biology