Author

Graham Johnson

Primary ORCID profile (0000-0002-1588-6241 · 1 paper)Unclaimed ORCID profile · follow to get notified of new preprints

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

Same name, identified by ORCID

Graham JohnsoniD1 paper

Biology Disciplines

Click to filter author papers

Bioinformatics· 1 Neuroscience· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Organism:human· 2 Assay:bulk RNA-seq· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Research Focus:drug response / drug discovery· 1 Approach:experimental assay· 1 Organism:mouse· 1

Frequent Co-Authors

Alexander S. GalkiniD· 1 shared Amal Dakka· 1 shared Anil K. ChekuriiD· 1 shared Aram J. KrausoniD· 1 shared Ashok RagavendraniD· 1 shared Christopher R. TrottaiD· 1 shared Dadi GaoiD· 1 shared Elisabetta MoriniiD· 1 shared

Activity by Year

2020-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

1 shared paperNeuroscience

Alexander S. GalkinORCID

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

Discovery and Preclinical Validation of a Clinically Optimized Mitochondrial Complex I Modulator for Alzheimer's Disease

Sergey Trushin, Thi Kim Oanh Nguyen, Mark Ostroot, Alexander S. Galkin, Toshihiko Nambara, Wenyan Lü, Takahisa Kanekiyo, Graham Johnson, Eugenia V. Trushina

This paper describes the discovery and validation of C273, a mitochondrial complex I modulator that reduces Alzheimer's disease pathology by enhancing cellular resilience through AMPK-mediated pathways.

bioRxiv · Apr 14, 2026 · PreprintNeuroscience

A deep learning approach to identify new gene targets of a novel therapeutic for human splicing disorders

Dadi Gao, Elisabetta Morini, Monica Salani, Aram J. Krauson, Ashok Ragavendran, Serkan Erdin, Emily M. Logan, Anil K. Chekuri, Wencheng Li, Amal Dakka, Nikolai A. Naryshkin, Christopher R. Trotta, Kerstin A. Effenberger, Matthew G. Woll, Vijayalakshmi Gabbeta, , Susan A. Slaugenhaupt

The paper uses deep learning to identify new gene targets for a splicing modulator drug, validating predictions with in vitro assays.

bioRxiv · Feb 3, 2020 · PreprintBioinformatics