Author

Miri Varshavsky

Hebrew University of JerusalemORCID 0009-0004-2155-5803Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2 Genomics· 1

Signature Assays, Organisms & Methods

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Research Focus:differential expression· 3 Assay:DNA methylation· 3 Organism:human· 3 Research Focus:benchmarking· 1 Approach:deep learning· 1 Research Focus:gene regulatory network inference· 1 Approach:machine learning (classical)· 1 Approach:statistical model· 1

Frequent Co-Authors

Tommy KaplaniD· 3 shared Benjamin GläseriD· 2 shared Ruth ShemeriD· 2 shared Yuval DoriD· 2 shared Alena van BömmeliD· 1 shared Amit Horn· 1 shared Anne RichmondiD· 1 shared Ayelet PeretziD· 1 shared

Activity by Year

2023-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 31 mutual co-author links

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3 shared papersBioinformatics

Tommy KaplanORCID

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3 papers

Recent·Most cited

An improved epigenetic age estimation with TFMethyl Clock reveals DNA methylation changes during aging in transcription factor binding sites

Tushar Patel, Robert J. Schwarz, Konstantin Riege, Miri Varshavsky, Anne Richmond, Riccardo Emilio Marioni, Hans Armin Kestler, Tommy Kaplan, Steve Hoffmann, Alena van Bömmel

The paper improves epigenetic age estimation by developing a TFMethyl Clock model that incorporates transcription factor binding sites, revealing DNA methylation changes linked to aging.

Nucleic Acids Research · Jul 3, 2026Peer-reviewedBioinformatics

Time is encoded by methylation changes at clustered CpG sites

Bracha-Lea Ochana, Daniel Nudelman, Daniel Cohen, Ayelet Peretz, Sheina Piyanzin, Ofer Gal-Rosenberg, Amit Horn, Netanel Loyfer, Miri Varshavsky, Ron Raisch, Ilona Shapiro, Yechiel Friedlander, Hagit Hochner, Benjamin Gläser, Yuval Dor, , Ruth Shemer

The paper shows that DNA methylation changes at clustered CpG sites encode chronological age with high accuracy using deep learning on blood samples.

Cell Reports · Jul 1, 2025Peer-reviewedGenomics

Accurate age prediction from blood using of small set of DNA methylation sites and a cohort-based machine learning algorithm

Miri Varshavsky, Gil Harari, Benjamin Gläser, Yuval Dor, Ruth Shemer, Tommy Kaplan

The paper introduces GP-age, a DNA methylation-based age prediction model using 30 CpG sites and a cohort-based machine learning approach, achieving high accuracy on both array and sequencing data.

Cell Reports Methods · Aug 28, 2023Peer-reviewedBioinformatics