Author

S.V. Vinogradova

Dana-Farber Cancer InstituteORCID 0000-0002-5419-8812Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Assay:ChIP-seq· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Organism:mouse· 1

Frequent Co-Authors

Alexander A. GimelbrantiD· 2 shared Andrey A. MironoviD· 1 shared Asia MendelevichiD· 1 shared Henry N. WardiD· 1 shared Sachit D. SaksenaiD· 1 shared Saumya GuptaiD· 1 shared Sébastien VigneauiD· 1 shared Shamil R. SunyaeviD· 1 shared

Activity by Year

2019-2020 · peak 1/yr

Co-Author Collaboration Network

8 top collaborators · 16 mutual co-author links

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2 shared papersBioinformatics

Alexander A. GimelbrantORCID

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2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintFeb 18, 2020

Unexpected variability of allelic imbalance estimates from RNA sequencing

Asia Mendelevich, S.V. Vinogradova, Saumya Gupta…·Alexander A. Gimelbrant

The paper assesses allelic imbalance variability in RNA sequencing and finds technical replicates show up to 7-fold higher variation than expected, which can be mitigated to improve differential analysis.

4 citations

bulk RNA-seqstatistical model

𝕏 PostBluesky

BioinformaticsBMC BioinformaticsPeer-reviewedFeb 28, 2019

MaGIC: a machine learning tool set and web application for monoallelic gene inference from chromatin

S.V. Vinogradova, Sachit D. Saksena, Henry N. Ward…·Alexander A. Gimelbrant

MaGIC identifies monoallelic expressed genes using chromatin signatures from ChIP-seq data, providing a tool for analyzing MAE in human and mouse cells.

7 citations

humanmouse

𝕏 PostBluesky