Author

Nikola Janakievski

Biotechnologisches Zentrum

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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Genomics· 2

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Research Focus:differential expression· 2 Assay:DNA methylation· 2 Organism:human· 2 Assay:bulk RNA-seq· 1 Assay:ChIP-seq· 1 Research Focus:gene regulatory network inference· 1 Approach:statistical model· 1

Frequent Co-Authors

Anna R. PoetschiD· 2 shared Pierre M. JoubertiD· 2 shared Anton VlasoviD· 1 shared Melissa SanabriaiD· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

4 top collaborators · 6 mutual co-author links

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2 shared papersGenomics

Anna R. PoetschORCID

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2 papers

Recent·Most cited

GenomicsBioinformaticsPeer-reviewedAug 1, 2026

Using the DNA language model, GROVER, to parse effects of sequence, chromatin and regulatory features on genome stability

Pierre M. Joubert, Anton Vlasov, Nikola Janakievski…·Anna R. Poetsch

The paper uses GROVER to analyze how DNA sequence, chromatin, and regulatory features influence genome stability by predicting DSB locations and identifying sequence tokens associated with DSB sensitivity.

1 citation

humanDNA methylation

𝕏 PostBluesky

GenomicsbioRxivPreprintJul 22, 2026

Using Deep Learning to predict replication timing reveals baseline control of genomic DNA sequence

Nikola Janakievski, Pierre M. Joubert, Anna R. Poetsch

This study uses deep learning to predict replication timing and finds DNA sequence provides sufficient information for prediction, with epigenetic features adding complementary value.

DOI 10.64898/2026.07.18.739304

humanDNA methylation

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