Author

J. Jubran

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Biology Disciplines

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Cancer Biology· 1

Signature Assays, Organisms & Methods

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Research Focus:gene regulatory network inference· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

E. Yeger-Lotem· 1 shared L. Rokach· 1 shared N. Rozenblum· 1 shared R. Slutsky· 1 shared U. Ben-David· 1 shared

Activity by Year

2023-2023 · peak 1/yr

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5 top collaborators · 10 mutual co-author links

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1 shared paperCancer Biology

E. Yeger-Lotem

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1 paper

Recent·Most cited

Machine-learning analysis of factors that shape cancer aneuploidy landscapes reveals an important role for negative selection

J. Jubran, R. Slutsky, N. Rozenblum, L. Rokach, U. Ben-David, E. Yeger-Lotem

This study uses machine learning to analyze cancer aneuploidy patterns, revealing that negative selection significantly shapes these landscapes, with tumor-suppressor gene density predicting gain patterns and oncogene density predicting loss patterns.

bioRxiv · Jul 5, 2023Cancer Biology