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Elior Rahmani

Showing results (1-10 of 38) with videos related to

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Frontiers in Bioinformatics|October 28, 2022
The Effect of Model Directionality on Cell-Type-Specific Differential DNA Methylation AnalysisElior Rahmani, Brandon Jew, Eran Halperin
Genome Biology|October 4, 2025
Unico: a unified model for cell-type resolution genomics from heterogeneous omics dataZeyuan Johnson Chen, Elior Rahmani, Eran Halperin
Genome Biology|July 14, 2019
CONFINED: distinguishing biological from technical sources of variation by leveraging multiple methylation datasetsMike Thompson, Zeyuan Johnson Chen, Elior Rahmani, et al.
Bioinformatics (Oxford, England)|September 9, 2017
Association testing of bisulfite-sequencing methylation data via a Laplace approximationOmer Weissbrod, Elior Rahmani, Regev Schweiger, et al.
Biorxiv : the Preprint Server for Biology|February 14, 2024
Highly parameterized polygenic scores tend to overfit to population stratification via random effectsAlan J Aw, Jeremy McRae, Elior Rahmani, et al.
Biorxiv : the Preprint Server for Biology|January 30, 2023
Phenotypic subtyping via contrastive learningAditya Gorla, Sriram Sankararaman, Esteban Burchard, et al.
Journal of Computational Biology : a Journal of Computational Molecular Cell Biology|June 23, 2018
Using Stochastic Approximation Techniques to Efficiently Construct Confidence Intervals for HeritabilityRegev Schweiger, Eyal Fisher, Elior Rahmani, et al.
Bioinformatics (Oxford, England)|June 17, 2014
EPIQ-efficient detection of SNP-SNP epistatic interactions for quantitative traitsYa'ara Arkin, Elior Rahmani, Marcus E Kleber, et al.
Bioinformatics (Oxford, England)|February 9, 2017
GLINT: a user-friendly toolset for the analysis of high-throughput DNA-methylation array dataElior Rahmani, Reut Yedidim, Liat Shenhav, et al.
Genome Biology|September 23, 2018
BayesCCE: a Bayesian framework for estimating cell-type composition from DNA methylation without the need for methylation referenceElior Rahmani, Regev Schweiger, Liat Shenhav, et al.
Pageof 4

Showing results (1-10 of 38) with videos related to

Sort By:
Pageof 4
Frontiers in Bioinformatics|October 28, 2022
The Effect of Model Directionality on Cell-Type-Specific Differential DNA Methylation AnalysisElior Rahmani, Brandon Jew, Eran Halperin
Genome Biology|October 4, 2025
Unico: a unified model for cell-type resolution genomics from heterogeneous omics dataZeyuan Johnson Chen, Elior Rahmani, Eran Halperin
Genome Biology|July 14, 2019
CONFINED: distinguishing biological from technical sources of variation by leveraging multiple methylation datasetsMike Thompson, Zeyuan Johnson Chen, Elior Rahmani, et al.
Bioinformatics (Oxford, England)|September 9, 2017
Association testing of bisulfite-sequencing methylation data via a Laplace approximationOmer Weissbrod, Elior Rahmani, Regev Schweiger, et al.
Biorxiv : the Preprint Server for Biology|February 14, 2024
Highly parameterized polygenic scores tend to overfit to population stratification via random effectsAlan J Aw, Jeremy McRae, Elior Rahmani, et al.
Biorxiv : the Preprint Server for Biology|January 30, 2023
Phenotypic subtyping via contrastive learningAditya Gorla, Sriram Sankararaman, Esteban Burchard, et al.
Journal of Computational Biology : a Journal of Computational Molecular Cell Biology|June 23, 2018
Using Stochastic Approximation Techniques to Efficiently Construct Confidence Intervals for HeritabilityRegev Schweiger, Eyal Fisher, Elior Rahmani, et al.
Bioinformatics (Oxford, England)|June 17, 2014
EPIQ-efficient detection of SNP-SNP epistatic interactions for quantitative traitsYa'ara Arkin, Elior Rahmani, Marcus E Kleber, et al.
Bioinformatics (Oxford, England)|February 9, 2017
GLINT: a user-friendly toolset for the analysis of high-throughput DNA-methylation array dataElior Rahmani, Reut Yedidim, Liat Shenhav, et al.
Genome Biology|September 23, 2018
BayesCCE: a Bayesian framework for estimating cell-type composition from DNA methylation without the need for methylation referenceElior Rahmani, Regev Schweiger, Liat Shenhav, et al.
Pageof 4