Author

Dmitry S. Kolobkov

Vavilov Institute of General GeneticsORCID 0000-0003-4225-2057Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Genetic & Genomic Medicine· 2 Bioinformatics· 1

Signature Assays, Organisms & Methods

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Organism:human· 2 Approach:statistical model· 2 Assay:whole-genome sequencing· 2 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Assay:GWAS summary statistics· 1 Approach:machine learning (classical)· 1 Research Focus:variant calling· 1

Frequent Co-Authors

Egor KosaretskiyiD· 2 shared Mikhail LebedeviD· 2 shared Ruslan VakhitoviD· 2 shared Александр Владимирович МедведевiD· 2 shared A. R. Malinowski· 1 shared Alexander Tischenko· 1 shared Andrew Ponomarev· 1 shared Daphne Lamirel· 1 shared

Activity by Year

2022-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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2 shared papersGenetic & Genomic Medicine

Egor KosaretskiyORCID

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3 papers

Recent·Most cited

Genetic & Genomic MedicineJournal of Translational MedicinePeer-reviewedApr 21, 2026

Identification of Novel Reproducible Combinatorial Genetic Risk Factors for Myalgic Encephalomyelitis in the DecodeME Patient Cohort and Commonalities with Long COVID

Jason M. Sardell, Sayoni Das, Matthew W Pearson…·Steve Gardner

This paper identifies 22,411 reproducible genetic signatures associated with ME in DecodeME cohorts and finds significant overlap with long COVID genes, suggesting shared mechanisms but distinct diseases.

1 citation

humanGWAS summary statistics

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Genetic & Genomic MedicineFrontiers in Big DataPeer-reviewedFeb 29, 2024

Efficacy of federated learning on genomic data: a study on the UK Biobank and the 1000 Genomes Project

Dmitry S. Kolobkov, Satyarth Mishra Sharma, Александр Владимирович Медведев…·Ruslan Vakhitov

This study evaluates federated learning's effectiveness on genomic data using UK Biobank and 1000 Genomes Project datasets, showing performance close to centralized models despite data heterogeneity.

34 citationstop 4%

humanwhole-genome sequencing

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BioinformaticsF1000ResearchPeer-reviewedMay 30, 2022

GRAPE: Genomic Relatedness Detection Pipeline

Александр Владимирович Медведев, Mikhail Lebedev, Andrew Ponomarev…·Pavel Nikonorov

GRAPE is a genomic relatedness detection pipeline that accurately classifies kinship degrees using preprocessing, IBD detection, and relationship estimation.

4 citations

whole-genome sequencingstatistical model

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