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Gregory Fonseca

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

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Journal of Chemical Theory and Computation|November 27, 2023
Force Field Analysis Software and Tools (FFAST): Assessing Machine Learning Force Fields under the MicroscopeGregory Fonseca, Igor Poltavsky, Alexandre Tkatchenko
The Journal of Chemical Physics|March 9, 2021
Challenges for machine learning force fields in reproducing potential energy surfaces of flexible moleculesValentin Vassilev-Galindo, Gregory Fonseca, Igor Poltavsky, et al.
The Journal of Chemical Physics|April 3, 2021
Improving molecular force fields across configurational space by combining supervised and unsupervised machine learningGregory Fonseca, Igor Poltavsky, Valentin Vassilev-Galindo, et al.
Toxicology Letters|November 30, 2023
Regulation of long non-coding RNA expression by aryl hydrocarbon receptor activationAeshah Alluli, Gregory Fonseca, Jason Matthews, et al.
Cell Reports|May 18, 2025
Machine-guided cell-fate engineeringEvan Appleton, Jenhan Tao, Songlei Liu, et al.
European Journal of Immunology|February 9, 2024
Induction of a memory-like CD4<sup>+</sup> T-cell phenotype by airway smooth muscle cellsJoyce H Jang, Michael Zhou, Kosuke Makita, et al.
The Journal of Experimental Medicine|October 4, 2017
Thrombospondin1 (TSP1) replacement prevents cerebral cavernous malformationsMiguel Alejandro Lopez-Ramirez, Gregory Fonseca, Hussein A Zeineddine, et al.
Nature Communications|December 2, 2022
DOT1L regulates chamber-specific transcriptional networks during cardiogenesis and mediates postnatal cell cycle withdrawalPaola Cattaneo, Michael G B Hayes, Nina Baumgarten, et al.
JCI Insight|February 8, 2019
Comprehensive transcriptome analysis of cerebral cavernous malformation across multiple species and genotypesJanne Koskimäki, Romuald Girard, Yan Li, et al.
Acta Neuropathologica Communications|August 21, 2019
Transcriptome clarifies mechanisms of lesion genesis versus progression in models of Ccm3 cerebral cavernous malformationsJanne Koskimäki, Dongdong Zhang, Yan Li, et al.
Pageof 1

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

Sort By:
Pageof 1
Journal of Chemical Theory and Computation|November 27, 2023
Force Field Analysis Software and Tools (FFAST): Assessing Machine Learning Force Fields under the MicroscopeGregory Fonseca, Igor Poltavsky, Alexandre Tkatchenko
The Journal of Chemical Physics|March 9, 2021
Challenges for machine learning force fields in reproducing potential energy surfaces of flexible moleculesValentin Vassilev-Galindo, Gregory Fonseca, Igor Poltavsky, et al.
The Journal of Chemical Physics|April 3, 2021
Improving molecular force fields across configurational space by combining supervised and unsupervised machine learningGregory Fonseca, Igor Poltavsky, Valentin Vassilev-Galindo, et al.
Toxicology Letters|November 30, 2023
Regulation of long non-coding RNA expression by aryl hydrocarbon receptor activationAeshah Alluli, Gregory Fonseca, Jason Matthews, et al.
Cell Reports|May 18, 2025
Machine-guided cell-fate engineeringEvan Appleton, Jenhan Tao, Songlei Liu, et al.
European Journal of Immunology|February 9, 2024
Induction of a memory-like CD4<sup>+</sup> T-cell phenotype by airway smooth muscle cellsJoyce H Jang, Michael Zhou, Kosuke Makita, et al.
The Journal of Experimental Medicine|October 4, 2017
Thrombospondin1 (TSP1) replacement prevents cerebral cavernous malformationsMiguel Alejandro Lopez-Ramirez, Gregory Fonseca, Hussein A Zeineddine, et al.
Nature Communications|December 2, 2022
DOT1L regulates chamber-specific transcriptional networks during cardiogenesis and mediates postnatal cell cycle withdrawalPaola Cattaneo, Michael G B Hayes, Nina Baumgarten, et al.
JCI Insight|February 8, 2019
Comprehensive transcriptome analysis of cerebral cavernous malformation across multiple species and genotypesJanne Koskimäki, Romuald Girard, Yan Li, et al.
Acta Neuropathologica Communications|August 21, 2019
Transcriptome clarifies mechanisms of lesion genesis versus progression in models of Ccm3 cerebral cavernous malformationsJanne Koskimäki, Dongdong Zhang, Yan Li, et al.
Pageof 1