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Best matches for Gábor Csányi:

The utility of Next Generation Sequencing for molecular diagnostics in Rett syndrome. Vidal S et al. Sci Rep. (2017)

Platelet-derived HMGB1 is a critical mediator of thrombosis. Vogel S et al. J Clin Invest. (2015)

Machine learning unifies the modeling of materials and molecules. Bartók AP et al. Sci Adv. (2017)

Search results

Items: 1 to 20 of 82

1.

Editorial: Oxidants and Redox Signaling in Inflammation.

Singla B, Holmdahl R, Csanyi G.

Front Immunol. 2019 Mar 26;10:545. doi: 10.3389/fimmu.2019.00545. eCollection 2019. No abstract available.

2.

Arterial Lymphatics in Atherosclerosis: Old Questions, New Insights, and Remaining Challenges.

Csányi G, Singla B.

J Clin Med. 2019 Apr 11;8(4). pii: E495. doi: 10.3390/jcm8040495. Review.

3.

Quantifying Chemical Structure and Machine-Learned Atomic Energies in Amorphous and Liquid Silicon.

Bernstein N, Bhattarai B, Csányi G, Drabold DA, Elliott SR, Deringer VL.

Angew Chem Int Ed Engl. 2019 May 20;58(21):7057-7061. doi: 10.1002/anie.201902625. Epub 2019 Apr 17.

PMID:
30835962
4.

Equation of State of Fluid Methane from First Principles with Machine Learning Potentials.

Veit M, Jain SK, Bonakala S, Rudra I, Hohl D, Csányi G.

J Chem Theory Comput. 2019 Apr 9;15(4):2574-2586. doi: 10.1021/acs.jctc.8b01242. Epub 2019 Mar 12.

PMID:
30794393
5.

Reactivity of Amorphous Carbon Surfaces: Rationalizing the Role of Structural Motifs in Functionalization Using Machine Learning.

Caro MA, Aarva A, Deringer VL, Csányi G, Laurila T.

Chem Mater. 2018 Nov 13;30(21):7446-7455. doi: 10.1021/acs.chemmater.8b03353. Epub 2018 Sep 10.

6.

PKCδ stimulates macropinocytosis via activation of SSH1-cofilin pathway.

Singla B, Lin HP, Ghoshal P, Cherian-Shaw M, Csányi G.

Cell Signal. 2019 Jan;53:111-121. doi: 10.1016/j.cellsig.2018.09.018. Epub 2018 Sep 24.

PMID:
30261270
7.

Preconditioners for the geometry optimisation and saddle point search of molecular systems.

Mones L, Ortner C, Csányi G.

Sci Rep. 2018 Sep 18;8(1):13991. doi: 10.1038/s41598-018-32105-x.

8.

Modeling the Phase-Change Memory Material, Ge2Sb2Te5, with a Machine-Learned Interatomic Potential.

Mocanu FC, Konstantinou K, Lee TH, Bernstein N, Deringer VL, Csányi G, Elliott SR.

J Phys Chem B. 2018 Sep 27;122(38):8998-9006. doi: 10.1021/acs.jpcb.8b06476. Epub 2018 Sep 14.

PMID:
30173522
9.

Sildenafil improves vascular endothelial function in patients with cystic fibrosis.

Rodriguez-Miguelez P, Lee N, Tucker MA, Csányi G, McKie KT, Forseen C, Harris RA.

Am J Physiol Heart Circ Physiol. 2018 Nov 1;315(5):H1486-H1494. doi: 10.1152/ajpheart.00301.2018. Epub 2018 Aug 31.

PMID:
30168731
10.

Data-driven learning and prediction of inorganic crystal structures.

Deringer VL, Proserpio DM, Csányi G, Pickard CJ.

Faraday Discuss. 2018 Oct 26;211(0):45-59. doi: 10.1039/c8fd00034d.

11.

Nested Transition Path Sampling.

Bolhuis PG, Csányi G.

Phys Rev Lett. 2018 Jun 22;120(25):250601. doi: 10.1103/PhysRevLett.120.250601.

PMID:
29979082
12.

Gaussian approximation potential modeling of lithium intercalation in carbon nanostructures.

Fujikake S, Deringer VL, Lee TH, Krynski M, Elliott SR, Csányi G.

J Chem Phys. 2018 Jun 28;148(24):241714. doi: 10.1063/1.5016317.

PMID:
29960342
13.

Comparison of permutationally invariant polynomials, neural networks, and Gaussian approximation potentials in representing water interactions through many-body expansions.

Nguyen TT, Székely E, Imbalzano G, Behler J, Csányi G, Ceriotti M, Götz AW, Paesani F.

J Chem Phys. 2018 Jun 28;148(24):241725. doi: 10.1063/1.5024577.

PMID:
29960316
14.

Identification of novel macropinocytosis inhibitors using a rational screen of Food and Drug Administration-approved drugs.

Lin HP, Singla B, Ghoshal P, Faulkner JL, Cherian-Shaw M, O'Connor PM, She JX, Belin de Chantemele EJ, Csányi G.

Br J Pharmacol. 2018 Sep;175(18):3640-3655. doi: 10.1111/bph.14429. Epub 2018 Aug 1.

PMID:
29953580
15.

Towards an atomistic understanding of disordered carbon electrode materials.

Deringer VL, Merlet C, Hu Y, Lee TH, Kattirtzi JA, Pecher O, Csányi G, Elliott SR, Grey CP.

Chem Commun (Camb). 2018 Jun 8;54(47):5988-5991. doi: 10.1039/c8cc01388h.

16.

Similarity Between Amorphous and Crystalline Phases: The Case of TiO2.

Mavračić J, Mocanu FC, Deringer VL, Csányi G, Elliott SR.

J Phys Chem Lett. 2018 Jun 7;9(11):2985-2990. doi: 10.1021/acs.jpclett.8b01067. Epub 2018 May 21.

17.

Growth Mechanism and Origin of High sp^{3} Content in Tetrahedral Amorphous Carbon.

Caro MA, Deringer VL, Koskinen J, Laurila T, Csányi G.

Phys Rev Lett. 2018 Apr 20;120(16):166101. doi: 10.1103/PhysRevLett.120.166101.

PMID:
29756912
18.

Data-Driven Learning of Total and Local Energies in Elemental Boron.

Deringer VL, Pickard CJ, Csányi G.

Phys Rev Lett. 2018 Apr 13;120(15):156001. doi: 10.1103/PhysRevLett.120.156001.

PMID:
29756876
19.

Realistic Atomistic Structure of Amorphous Silicon from Machine-Learning-Driven Molecular Dynamics.

Deringer VL, Bernstein N, Bartók AP, Cliffe MJ, Kerber RN, Marbella LE, Grey CP, Elliott SR, Csányi G.

J Phys Chem Lett. 2018 Jun 7;9(11):2879-2885. doi: 10.1021/acs.jpclett.8b00902. Epub 2018 May 17.

20.

PKCδ-Mediated Nox2 Activation Promotes Fluid-Phase Pinocytosis of Antigens by Immature Dendritic Cells.

Singla B, Ghoshal P, Lin H, Wei Q, Dong Z, Csányi G.

Front Immunol. 2018 Mar 26;9:537. doi: 10.3389/fimmu.2018.00537. eCollection 2018.

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