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Michael Elgart

Showing results (11-20 of 21) with videos related to

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Development (Cambridge, England)|November 14, 2008
Dual requirement for Pax6 in retinal progenitor cellsVarda Oron-Karni, Chen Farhy, Michael Elgart, et al.
Plos Biology|May 28, 2024
Organ transformation by environmental disruption of protein integrity and epigenetic memory in DrosophilaOrli Snir, Michael Elgart, Yulia Gnainsky, et al.
Plos One|January 27, 2026
CoSMIC: A hybrid approach for large-scale, high-resolution microbial profiling of novel nichesMaor Knafo, Shahar Rezenman, Tal Idan, et al.
HGG Advances|May 9, 2024
A parametric bootstrap approach for computing confidence intervals for genetic correlations with application to genetically determined protein-protein networksYi-Ting Tsai, Yana Hrytsenko, Michael Elgart, et al.
Ebiomedicine|November 25, 2023
Anaerobic pathogens associated with OSA may contribute to pathophysiology via amino-acid depletionMichael Elgart, Ying Zhang, Yuan Zhang, et al.
Ebiomedicine|September 29, 2022
Genetic determinants of cardiometabolic and pulmonary phenotypes and obstructive sleep apnoea in HCHS/SOLYuan Zhang, Michael Elgart, Nuzulul Kurniansyah, et al.
Ebiomedicine|December 9, 2022
Genetic associations between sleep traits and cognitive ageing outcomes in the Hispanic Community Health Study/Study of LatinosYuan Zhang, Michael Elgart, Einat Granot-Hershkovitz, et al.
Cell Reports. Medicine|December 13, 2022
Correlations between complex human phenotypes vary by genetic background, gender, and environmentMichael Elgart, Matthew O Goodman, Carmen Isasi, et al.
Communications Biology|August 22, 2022
Non-linear machine learning models incorporating SNPs and PRS improve polygenic prediction in diverse human populationsMichael Elgart, Genevieve Lyons, Santiago Romero-Brufau, et al.
Scientific Reports|May 30, 2024
Machine learning models for predicting blood pressure phenotypes by combining multiple polygenic risk scoresYana Hrytsenko, Benjamin Shea, Michael Elgart, et al.
Pageof 3

Showing results (11-20 of 21) with videos related to

Sort By:
Pageof 3
Development (Cambridge, England)|November 14, 2008
Dual requirement for Pax6 in retinal progenitor cellsVarda Oron-Karni, Chen Farhy, Michael Elgart, et al.
Plos Biology|May 28, 2024
Organ transformation by environmental disruption of protein integrity and epigenetic memory in DrosophilaOrli Snir, Michael Elgart, Yulia Gnainsky, et al.
Plos One|January 27, 2026
CoSMIC: A hybrid approach for large-scale, high-resolution microbial profiling of novel nichesMaor Knafo, Shahar Rezenman, Tal Idan, et al.
HGG Advances|May 9, 2024
A parametric bootstrap approach for computing confidence intervals for genetic correlations with application to genetically determined protein-protein networksYi-Ting Tsai, Yana Hrytsenko, Michael Elgart, et al.
Ebiomedicine|November 25, 2023
Anaerobic pathogens associated with OSA may contribute to pathophysiology via amino-acid depletionMichael Elgart, Ying Zhang, Yuan Zhang, et al.
Ebiomedicine|September 29, 2022
Genetic determinants of cardiometabolic and pulmonary phenotypes and obstructive sleep apnoea in HCHS/SOLYuan Zhang, Michael Elgart, Nuzulul Kurniansyah, et al.
Ebiomedicine|December 9, 2022
Genetic associations between sleep traits and cognitive ageing outcomes in the Hispanic Community Health Study/Study of LatinosYuan Zhang, Michael Elgart, Einat Granot-Hershkovitz, et al.
Cell Reports. Medicine|December 13, 2022
Correlations between complex human phenotypes vary by genetic background, gender, and environmentMichael Elgart, Matthew O Goodman, Carmen Isasi, et al.
Communications Biology|August 22, 2022
Non-linear machine learning models incorporating SNPs and PRS improve polygenic prediction in diverse human populationsMichael Elgart, Genevieve Lyons, Santiago Romero-Brufau, et al.
Scientific Reports|May 30, 2024
Machine learning models for predicting blood pressure phenotypes by combining multiple polygenic risk scoresYana Hrytsenko, Benjamin Shea, Michael Elgart, et al.
Pageof 3