Author

Victoria D. Turubanova

Sirius University of Science and TechnologyORCID 0000-0002-4648-0738Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1

Signature Assays, Organisms & Methods

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Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Research Focus:differential expression· 1 Research Focus:drug response / drug discovery· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Approach:statistical model· 1

Frequent Co-Authors

Arseniy TrukhanoviD· 1 shared Mikhail IvanchenkoiD· 1 shared Mikhail KrivonosoviD· 1 shared Olga VershininaiD· 1 shared

Activity by Year

2025-2025 · peak 1/yr

Co-Author Collaboration Network

4 top collaborators · 6 mutual co-author links

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1 shared paperBioinformatics

Arseniy TrukhanovORCID

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1 paper

Recent·Most cited

Explainable machine learning models for glioma subtype classification and survival prediction

Olga Vershinina, Victoria D. Turubanova, Mikhail Krivonosov, Arseniy Trukhanov, Mikhail Ivanchenko

This paper develops explainable machine learning models to classify glioma subtypes and predict survival using RNA-seq data, achieving high accuracy and transparency.

Cancers · Aug 9, 2025Peer-reviewedBioinformatics