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Fengdan Ye

Showing results (1-10 of 9) with videos related to

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Proceedings of the National Academy of Sciences of the United States of America|February 9, 2019
Machine-learning approach to the design of OSDAs for zeolite betaFrits Daeyaert, Fengdan Ye, Michael W Deem
Developmental Cognitive Neuroscience|October 21, 2022
Task-based co-activation patterns reliably predict resting state canonical network engagement during developmentFengdan Ye, Robert Kohler, Bianca Serio, et al.
Oncotarget|March 31, 2018
Modularity of the metabolic gene network as a prognostic biomarker for hepatocellular carcinomaFengdan Ye, Dongya Jia, Mingyang Lu, et al.
Developmental Cognitive Neuroscience|December 10, 2022
A multidimensional approach to understanding the emergence of sex differences in internalizing symptoms in adolescenceBianca Serio, Robert Kohler, Fengdan Ye, et al.
Brain Communications|September 12, 2022
In Alzheimer-prone brain regions, metabolism and risk-gene expression are strongly correlatedFengdan Ye, Quentin Funk, Elijah Rockers, et al.
Molecular Psychiatry|June 12, 2023
Distinct neural networks predict cocaine versus cannabis treatment outcomesSarah D Lichenstein, Robert Kohler, Fengdan Ye, et al.
Frontiers in Human Neuroscience|September 21, 2018
Corrigendum: Static and Dynamic Measures of Human Brain Connectivity Predict Complementary Aspects of Human Cognitive PerformanceAurora I Ramos-Nuñez, Simon Fischer-Baum, Randi C Martin, et al.
Frontiers in Human Neuroscience|September 9, 2017
Static and Dynamic Measures of Human Brain Connectivity Predict Complementary Aspects of Human Cognitive PerformanceAurora I Ramos-Nuñez, Simon Fischer-Baum, Randi C Martin, et al.
Journal of Cognitive Neuroscience|May 5, 2017
Brain Modularity Mediates the Relation between Task Complexity and PerformanceQiuhai Yue, Randi C Martin, Simon Fischer-Baum, et al.
Pageof 1

Showing results (1-10 of 9) with videos related to

Sort By:
Pageof 1
Proceedings of the National Academy of Sciences of the United States of America|February 9, 2019
Machine-learning approach to the design of OSDAs for zeolite betaFrits Daeyaert, Fengdan Ye, Michael W Deem
Developmental Cognitive Neuroscience|October 21, 2022
Task-based co-activation patterns reliably predict resting state canonical network engagement during developmentFengdan Ye, Robert Kohler, Bianca Serio, et al.
Oncotarget|March 31, 2018
Modularity of the metabolic gene network as a prognostic biomarker for hepatocellular carcinomaFengdan Ye, Dongya Jia, Mingyang Lu, et al.
Developmental Cognitive Neuroscience|December 10, 2022
A multidimensional approach to understanding the emergence of sex differences in internalizing symptoms in adolescenceBianca Serio, Robert Kohler, Fengdan Ye, et al.
Brain Communications|September 12, 2022
In Alzheimer-prone brain regions, metabolism and risk-gene expression are strongly correlatedFengdan Ye, Quentin Funk, Elijah Rockers, et al.
Molecular Psychiatry|June 12, 2023
Distinct neural networks predict cocaine versus cannabis treatment outcomesSarah D Lichenstein, Robert Kohler, Fengdan Ye, et al.
Frontiers in Human Neuroscience|September 21, 2018
Corrigendum: Static and Dynamic Measures of Human Brain Connectivity Predict Complementary Aspects of Human Cognitive PerformanceAurora I Ramos-Nuñez, Simon Fischer-Baum, Randi C Martin, et al.
Frontiers in Human Neuroscience|September 9, 2017
Static and Dynamic Measures of Human Brain Connectivity Predict Complementary Aspects of Human Cognitive PerformanceAurora I Ramos-Nuñez, Simon Fischer-Baum, Randi C Martin, et al.
Journal of Cognitive Neuroscience|May 5, 2017
Brain Modularity Mediates the Relation between Task Complexity and PerformanceQiuhai Yue, Randi C Martin, Simon Fischer-Baum, et al.
Pageof 1