Author

Kathrin Reichwald

Leibniz Institute on Aging - Fritz Lipmann Institute (FLI)

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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Signature Assays, Organisms & Methods

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Assay:bulk RNA-seq· 2 Research Focus:differential expression· 2 Organism:zebrafish· 2 Research Focus:benchmarking· 1 Approach:deep learning· 1 Research Focus:gene regulatory network inference· 1 Research Focus:software / tool· 1 Approach:statistical model· 1

Frequent Co-Authors

Alessandro CellerinoiD· 2 shared Marco GrothiD· 2 shared Philipp KochiD· 2 shared Alessandro Ori‬‬iD· 1 shared Elisa Ferrari· 1 shared Erika Kelmer SacramentoiD· 1 shared Mariateresa MazzettoiD· 1 shared Mario BaumgartiD· 1 shared

Activity by Year

2022-2023 · peak 1/yr

Co-Author Collaboration Network

8 top collaborators · 22 mutual co-author links

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2 shared papersGenomics

Alessandro CellerinoORCID

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2 papers

Recent·Most cited

Transcriptome analysis of different strains of the turquoise killifish Nothobranchius furzeri identifies signatures associated with heritable lifespan differences

Mariateresa Mazzetto, Kathrin Reichwald, Erika Kelmer Sacramento, Philipp Koch, Alessandro Ori‬‬, Marco Groth, Alessandro Cellerino

bioRxiv · Nov 20, 2023 · PreprintGenomics

A deep neural network provides an ultraprecise transcriptomic clock of the short-lived fish Nothobranchius furzeri and identifies predictive genes translatable to human aging.

Elisa Ferrari, Kathrin Reichwald, Philipp Koch, Marco Groth, Mario Baumgart, Alessandro Cellerino

The paper develops a deep learning model called SA-DNN to create an ultraprecise transcriptomic aging clock in the short-lived fish N. furzeri and translates it to human aging with 3-year accuracy.

bioRxiv · Nov 26, 2022 · PreprintGenomics