Author

I. Siekmann

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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Paleontology· 1 Physiology· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 1 Approach:experimental assay· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Assay:proteomics· 1

Frequent Co-Authors

C. A. Stead· 1 shared I. Jarman· 1 shared J. A. Strauss· 1 shared J. G. Burniston· 1 shared J. N. Lallensack· 1 shared K. Hesketh· 1 shared K. Srisawat· 1 shared M. Cocks· 1 shared

Activity by Year

2023-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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1 shared paperPhysiology

C. A. Stead

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2 papers

Recent·Most cited

Classification of dinosaur footprints using machine learning

M. Jones, J. N. Lallensack, I. Jarman, P. Falkingham, I. Siekmann

The paper trains machine learning models to classify dinosaur footprints as ornithopods or theropods using 20 landmark features, finding that MLP performs best with class imbalance.

bioRxiv · Jul 15, 2024Paleontology

Muscle of obese insulin-resistant humans exhibits losses in proteostasis and attenuated proteome dynamics that are improved by exercise training.

K. Srisawat, C. A. Stead, K. Hesketh, M. Pogson, J. A. Strauss, M. Cocks, I. Siekmann, S. M. Phillips, P. J. Lisboa, S. Shepherd, J. G. Burniston

This study examines muscle proteostasis in obese insulin-resistant individuals and finds that endurance exercise improves proteome dynamics and proteostasis.

bioRxiv · Mar 16, 2023 · PreprintPhysiology