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Gil Ben Cohen

Showing results (1-10 of 5) with videos related to

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Cancer Research|October 20, 2022
Shared Cancer Dataset Analysis Identifies and Predicts the Quantitative Effects of Pan-Cancer Somatic Driver VariantsJakob Landau, Linoy Tsaban, Adar Yaacov, et al.
Cell Reports. Medicine|June 12, 2024
Cancer mutational signatures identification in clinical assays using neural embedding-based representationsAdar Yaacov, Gil Ben Cohen, Jakob Landau, et al.
Briefings in Bioinformatics|January 19, 2022
TP53_PROF: a machine learning model to predict impact of missense mutations in TP53Gil Ben-Cohen, Flora Doffe, Michal Devir, et al.
Molecular Oncology|January 25, 2023
Concordance between cancer gene alterations in tumor and circulating tumor DNA correlates with poor survival in a real-world precision-medicine populationShai Rosenberg, Gil Ben Cohen, Shumei Kato, et al.
Computers in Biology and Medicine|December 19, 2024
Graph convolution networks model identifies and quantifies gene and cancer specific transcriptome signatures of cancer driver eventsGil Ben Cohen, Adar Yaacov, Yishai Ben Zvi, et al.
Pageof 1

Showing results (1-10 of 5) with videos related to

Sort By:
Pageof 1
Cancer Research|October 20, 2022
Shared Cancer Dataset Analysis Identifies and Predicts the Quantitative Effects of Pan-Cancer Somatic Driver VariantsJakob Landau, Linoy Tsaban, Adar Yaacov, et al.
Cell Reports. Medicine|June 12, 2024
Cancer mutational signatures identification in clinical assays using neural embedding-based representationsAdar Yaacov, Gil Ben Cohen, Jakob Landau, et al.
Briefings in Bioinformatics|January 19, 2022
TP53_PROF: a machine learning model to predict impact of missense mutations in TP53Gil Ben-Cohen, Flora Doffe, Michal Devir, et al.
Molecular Oncology|January 25, 2023
Concordance between cancer gene alterations in tumor and circulating tumor DNA correlates with poor survival in a real-world precision-medicine populationShai Rosenberg, Gil Ben Cohen, Shumei Kato, et al.
Computers in Biology and Medicine|December 19, 2024
Graph convolution networks model identifies and quantifies gene and cancer specific transcriptome signatures of cancer driver eventsGil Ben Cohen, Adar Yaacov, Yishai Ben Zvi, et al.
Pageof 1