Author

K. Gayvert

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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Cancer Biology· 1 Evolutionary Biology· 1

Signature Assays, Organisms & Methods

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Organism:human· 2 Assay:bulk RNA-seq· 1 Research Focus:chromatin & epigenetic regulation· 1 Research Focus:drug response / drug discovery· 1 Research Focus:gene regulatory network inference· 1 Approach:machine learning (classical)· 1 Approach:statistical model· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

A. Baum· 1 shared A. Perez· 1 shared C. A. Kyratsous· 1 shared C. Gilvary· 1 shared C. S. Leslie· 1 shared G. Pandey· 1 shared G. S. Atwal· 1 shared I. Setliff· 1 shared

Activity by Year

2019-2021 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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1 shared paperEvolutionary Biology

A. Baum

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Author profile →

2 papers

Recent·Most cited

Viral population genomics reveals host and infectivity impact on SARS-CoV-2 adaptive landscape

K. Gayvert, R. Copin, S. McKay, I. Setliff, W. K. Lim, A. Baum, C. A. Kyratsous, G. S. Atwal

The paper analyzes SARS-CoV-2 genomic diversity to identify sites under selection, showing purifying selection dominates with some diversifying pressure, particularly in the spike protein and T cell epitopes.

bioRxiv · Dec 30, 2021 · PreprintEvolutionary Biology

A machine learning approach predicts essential genes and pharmacological targets in cancer

C. Gilvary, N. Madhukar, K. Gayvert, M. Foronda, A. Perez, C. S. Leslie, L. Dow, G. Pandey, O. Elemento

This paper introduces ECLIPSE, a machine learning model that predicts essential genes and pharmacological targets in cancer by integrating genomic, cell line, and experimental features, showing better differentiation of approved cancer drugs from non-approved ones.

bioRxiv · Jul 4, 2019 · PreprintCancer Biology