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Hossein Sharifi Noghabi

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

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IET Systems Biology|November 24, 2016
Robust group fused lasso for multisample copy number variation detection under uncertaintyHossein Sharifi Noghabi, Majid Mohammadi, Yao-Hua Tan
Bioinformatics (Oxford, England)|September 13, 2019
MOLI: multi-omics late integration with deep neural networks for drug response predictionHossein Sharifi-Noghabi, Olga Zolotareva, Colin C Collins, et al.
Genomics|January 15, 2016
Robust and stable gene selection via Maximum-Minimum Correntropy CriterionMajid Mohammadi, Hossein Sharifi Noghabi, Ghosheh Abed Hodtani, et al.
Bioinformatics (Oxford, England)|July 14, 2020
AITL: Adversarial Inductive Transfer Learning with input and output space adaptation for pharmacogenomicsHossein Sharifi-Noghabi, Shuman Peng, Olga Zolotareva, et al.
Briefings in Bioinformatics|August 12, 2021
Drug sensitivity prediction from cell line-based pharmacogenomics data: guidelines for developing machine learning modelsHossein Sharifi-Noghabi, Soheil Jahangiri-Tazehkand, Petr Smirnov, et al.
Pageof 1

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

Sort By:
Pageof 1
IET Systems Biology|November 24, 2016
Robust group fused lasso for multisample copy number variation detection under uncertaintyHossein Sharifi Noghabi, Majid Mohammadi, Yao-Hua Tan
Bioinformatics (Oxford, England)|September 13, 2019
MOLI: multi-omics late integration with deep neural networks for drug response predictionHossein Sharifi-Noghabi, Olga Zolotareva, Colin C Collins, et al.
Genomics|January 15, 2016
Robust and stable gene selection via Maximum-Minimum Correntropy CriterionMajid Mohammadi, Hossein Sharifi Noghabi, Ghosheh Abed Hodtani, et al.
Bioinformatics (Oxford, England)|July 14, 2020
AITL: Adversarial Inductive Transfer Learning with input and output space adaptation for pharmacogenomicsHossein Sharifi-Noghabi, Shuman Peng, Olga Zolotareva, et al.
Briefings in Bioinformatics|August 12, 2021
Drug sensitivity prediction from cell line-based pharmacogenomics data: guidelines for developing machine learning modelsHossein Sharifi-Noghabi, Soheil Jahangiri-Tazehkand, Petr Smirnov, et al.
Pageof 1