Author

Vanesa Getseva

Columbia UniversityORCID 0009-0009-6651-0218Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

Click to filter author papers

Signature Assays, Organisms & Methods

Click to filter · or open tag

Approach:statistical model· 2 Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1 Assay:imaging· 1

Frequent Co-Authors

Alexandros SigarasiD· 1 shared Anastasia V. StolyarovaiD· 1 shared Iman HajirasoulihaiD· 1 shared Ipsita AgarwaliD· 1 shared Juan Miguel MosqueraiD· 1 shared Majd Al AssaadiD· 1 shared Matthew BrendeliD· 1 shared Michael SigourosiD· 1 shared

Activity by Year

2022-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

1 shared paperBioinformatics

Alexandros SigarasORCID

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

GenomicsbioRxivPreprintSep 2, 2026

A sibling study of variation in parental mutation rates

Vanesa Getseva, Pelin POYRAZ, Anastasia V. Stolyarova…·Molly Przeworski

The paper identifies de novo mutations in siblings and finds no differences in mutation rates by ancestry or smoking status, but links disruptions in REV1 and LIG1 to increased germline mutation rates.

DOI 10.64898/2026.05.10.724105

humanwhole-genome sequencing

𝕏 PostBluesky

BioinformaticsEBioMedicinePeer-reviewedMay 26, 2022

Weakly-Supervised Tumor Purity Prediction FromFrozen H&E Stained Slides

Matthew Brendel, Vanesa Getseva, Majd Al Assaad…·Iman Hajirasouliha

This paper introduces a weakly-supervised method to predict tumor purity from H&E stained slides, achieving high accuracy and enabling clinical applications.

22 citations

imagingdeep learning

𝕏 PostBluesky