Müller KR - Search Results

1

Optimizing transition states via kernel-based machine learning.

Pozun ZD, Hansen K, Sheppard D, Rupp M, Müller KR, Henkelman G. Pozun ZD, et al. Among authors: muller kr. J Chem Phys. 2012 May 7;136(17):174101. doi: 10.1063/1.4707167. J Chem Phys. 2012. PMID: 22583204

2

Classifying 'drug-likeness' with kernel-based learning methods.

Müller KR, Rätsch G, Sonnenburg S, Mika S, Grimm M, Heinrich N. Müller KR, et al. J Chem Inf Model. 2005 Mar-Apr;45(2):249-53. doi: 10.1021/ci049737o. J Chem Inf Model. 2005. PMID: 15807485

3

A probabilistic approach to classifying metabolic stability.

Schwaighofer A, Schroeter T, Mika S, Hansen K, Ter Laak A, Lienau P, Reichel A, Heinrich N, Müller KR. Schwaighofer A, et al. Among authors: muller kr. J Chem Inf Model. 2008 Apr;48(4):785-96. doi: 10.1021/ci700142c. Epub 2008 Mar 8. J Chem Inf Model. 2008. PMID: 18327900

4

Benchmark data set for in silico prediction of Ames mutagenicity.

Hansen K, Mika S, Schroeter T, Sutter A, ter Laak A, Steger-Hartmann T, Heinrich N, Müller KR. Hansen K, et al. Among authors: muller kr. J Chem Inf Model. 2009 Sep;49(9):2077-81. doi: 10.1021/ci900161g. J Chem Inf Model. 2009. PMID: 19702240

5

From machine learning to natural product derivatives that selectively activate transcription factor PPARgamma.

Rupp M, Schroeter T, Steri R, Zettl H, Proschak E, Hansen K, Rau O, Schwarz O, Müller-Kuhrt L, Schubert-Zsilavecz M, Müller KR, Schneider G. Rupp M, et al. Among authors: muller kuhrt l, muller kr. ChemMedChem. 2010 Feb 1;5(2):191-4. doi: 10.1002/cmdc.200900469. ChemMedChem. 2010. PMID: 20043315 No abstract available.

6

Truxillic acid derivatives act as peroxisome proliferator-activated receptor gamma activators.

Steri R, Rupp M, Proschak E, Schroeter T, Zettl H, Hansen K, Schwarz O, Müller-Kuhrt L, Müller KR, Schneider G, Schubert-Zsilavecz M. Steri R, et al. Among authors: muller kuhrt l, muller kr. Bioorg Med Chem Lett. 2010 May 1;20(9):2920-3. doi: 10.1016/j.bmcl.2010.03.026. Epub 2010 Mar 7. Bioorg Med Chem Lett. 2010. PMID: 20347594

7

StructRank: a new approach for ligand-based virtual screening.

Rathke F, Hansen K, Brefeld U, Müller KR. Rathke F, et al. Among authors: muller kr. J Chem Inf Model. 2011 Jan 24;51(1):83-92. doi: 10.1021/ci100308f. Epub 2010 Dec 17. J Chem Inf Model. 2011. PMID: 21166393

8

Fast and accurate modeling of molecular atomization energies with machine learning.

Rupp M, Tkatchenko A, Müller KR, von Lilienfeld OA. Rupp M, et al. Among authors: muller kr. Phys Rev Lett. 2012 Feb 3;108(5):058301. doi: 10.1103/PhysRevLett.108.058301. Epub 2012 Jan 31. Phys Rev Lett. 2012. PMID: 22400967 Free article.

9

Finding density functionals with machine learning.

Snyder JC, Rupp M, Hansen K, Müller KR, Burke K. Snyder JC, et al. Among authors: muller kr. Phys Rev Lett. 2012 Jun 22;108(25):253002. doi: 10.1103/PhysRevLett.108.253002. Epub 2012 Jun 19. Phys Rev Lett. 2012. PMID: 23004593

10

Orbital-free bond breaking via machine learning.

Snyder JC, Rupp M, Hansen K, Blooston L, Müller KR, Burke K. Snyder JC, et al. Among authors: muller kr. J Chem Phys. 2013 Dec 14;139(22):224104. doi: 10.1063/1.4834075. J Chem Phys. 2013. PMID: 24329053 Free article.

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