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Proceedings of the National Academy of Sciences of the United States of America
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February 15, 2020
Veridical data science
Bin Yu, Karl Kumbier
Proceedings of the National Academy of Sciences of the United States of America
|
January 21, 2018
Iterative random forests to discover predictive and stable high-order interactions
Sumanta Basu, Karl Kumbier, James B Brown, et al.
ACS Chemical Biology
|
March 15, 2023
Selection of Optimal Cell Lines for High-Content Phenotypic Screening
Louise Heinrich, Karl Kumbier, Li Li, et al.
Biorxiv : the Preprint Server for Biology
|
January 30, 2023
Selection of optimal cell lines for high-content phenotypic screening
Louise Heinrich, Karl Kumbier, Li Li, et al.
Proceedings of the National Academy of Sciences of the United States of America
|
October 18, 2019
Definitions, methods, and applications in interpretable machine learning
W James Murdoch, Chandan Singh, Karl Kumbier, et al.
Cancer Research Communications
|
December 19, 2024
Targeting PRMT1 Reduces Cancer Persistence and Tumor Relapse in EGFR- and KRAS-Mutant Lung Cancer
Xiaoxiao Sun, Karl Kumbier, Savitha Gayathri, et al.
Science Advances
|
June 12, 2026
ResMap: A community resource for systematic mapping of therapy-persistent residual cancer cell dependencies across contexts
Xiaoxiao Sun, Savitha Gayathri, Karl Kumbier, et al.
Scientific Reports
|
October 8, 2021
A novel random forest approach to revealing interactions and controls on chlorophyll concentration and bacterial communities during coastal phytoplankton blooms
Yiwei Cheng, Ved N Bhoot, Karl Kumbier, et al.
Cell Reports
|
May 4, 2023
Dissecting the effects of GTPase and kinase domain mutations on LRRK2 endosomal localization and activity
Capria Rinaldi, Christopher S Waters, Zizheng Li, et al.
Plos One
|
April 16, 2024
Learning epistatic polygenic phenotypes with Boolean interactions
Merle Behr, Karl Kumbier, Aldo Cordova-Palomera, et al.
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Search research articles
Search
Showing results (1-10 of 14) with videos related to
Sort By:
Page
of 2
Proceedings of the National Academy of Sciences of the United States of America
|
February 15, 2020
Veridical data science
Bin Yu, Karl Kumbier
Proceedings of the National Academy of Sciences of the United States of America
|
January 21, 2018
Iterative random forests to discover predictive and stable high-order interactions
Sumanta Basu, Karl Kumbier, James B Brown, et al.
ACS Chemical Biology
|
March 15, 2023
Selection of Optimal Cell Lines for High-Content Phenotypic Screening
Louise Heinrich, Karl Kumbier, Li Li, et al.
Biorxiv : the Preprint Server for Biology
|
January 30, 2023
Selection of optimal cell lines for high-content phenotypic screening
Louise Heinrich, Karl Kumbier, Li Li, et al.
Proceedings of the National Academy of Sciences of the United States of America
|
October 18, 2019
Definitions, methods, and applications in interpretable machine learning
W James Murdoch, Chandan Singh, Karl Kumbier, et al.
Cancer Research Communications
|
December 19, 2024
Targeting PRMT1 Reduces Cancer Persistence and Tumor Relapse in EGFR- and KRAS-Mutant Lung Cancer
Xiaoxiao Sun, Karl Kumbier, Savitha Gayathri, et al.
Science Advances
|
June 12, 2026
ResMap: A community resource for systematic mapping of therapy-persistent residual cancer cell dependencies across contexts
Xiaoxiao Sun, Savitha Gayathri, Karl Kumbier, et al.
Scientific Reports
|
October 8, 2021
A novel random forest approach to revealing interactions and controls on chlorophyll concentration and bacterial communities during coastal phytoplankton blooms
Yiwei Cheng, Ved N Bhoot, Karl Kumbier, et al.
Cell Reports
|
May 4, 2023
Dissecting the effects of GTPase and kinase domain mutations on LRRK2 endosomal localization and activity
Capria Rinaldi, Christopher S Waters, Zizheng Li, et al.
Plos One
|
April 16, 2024
Learning epistatic polygenic phenotypes with Boolean interactions
Merle Behr, Karl Kumbier, Aldo Cordova-Palomera, et al.
Page
of 2