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Items: 17

1.

Development of CDK-targeted scoring functions for prediction of binding affinity.

Levin NMB, Pintro VO, Bitencourt-Ferreira G, de Mattos BB, de Castro Silvério A, de Azevedo WF Jr.

Biophys Chem. 2018 Apr;235:1-8. doi: 10.1016/j.bpc.2018.01.004. Epub 2018 Feb 1.

PMID:
29407904
2.

The Ink4a/Arf locus operates as a regulator of the circadian clock modulating RAS activity.

El-Athman R, Genov NN, Mazuch J, Zhang K, Yu Y, Fuhr L, Abreu M, Li Y, Wallach T, Kramer A, Schmitt CA, Relógio A.

PLoS Biol. 2017 Dec 7;15(12):e2002940. doi: 10.1371/journal.pbio.2002940. eCollection 2017 Dec.

3.

Supervised machine learning techniques to predict binding affinity. A study for cyclin-dependent kinase 2.

de Ávila MB, Xavier MM, Pintro VO, de Azevedo WF Jr.

Biochem Biophys Res Commun. 2017 Dec 9;494(1-2):305-310. doi: 10.1016/j.bbrc.2017.10.035. Epub 2017 Oct 7.

PMID:
29017921
4.

Performance of in silico tools for the evaluation of p16INK4a (CDKN2A) variants in CAGI.

Carraro M, Minervini G, Giollo M, Bromberg Y, Capriotti E, Casadio R, Dunbrack R, Elefanti L, Fariselli P, Ferrari C, Gough J, Katsonis P, Leonardi E, Lichtarge O, Menin C, Martelli PL, Niroula A, Pal LR, Repo S, Scaini MC, Vihinen M, Wei Q, Xu Q, Yang Y, Yin Y, Zaucha J, Zhao H, Zhou Y, Brenner SE, Moult J, Tosatto SCE.

Hum Mutat. 2017 Sep;38(9):1042-1050. doi: 10.1002/humu.23235. Epub 2017 May 16.

5.

Blind prediction of deleterious amino acid variations with SNPs&GO.

Capriotti E, Martelli PL, Fariselli P, Casadio R.

Hum Mutat. 2017 Sep;38(9):1064-1071. doi: 10.1002/humu.23179. Epub 2017 May 2.

6.

Understanding the Structural Basis for Inhibition of Cyclin-Dependent Kinases. New Pieces in the Molecular Puzzle.

Levin NMB, Pintro VO, de Avila MB, de Mattos BB, De Azevedo WF Jr.

Curr Drug Targets. 2017;18(9):1104-1111. doi: 10.2174/1389450118666161116130155. Review.

PMID:
27848884
7.

Radiogenomics of Glioblastoma: Machine Learning-based Classification of Molecular Characteristics by Using Multiparametric and Multiregional MR Imaging Features.

Kickingereder P, Bonekamp D, Nowosielski M, Kratz A, Sill M, Burth S, Wick A, Eidel O, Schlemmer HP, Radbruch A, Debus J, Herold-Mende C, Unterberg A, Jones D, Pfister S, Wick W, von Deimling A, Bendszus M, Capper D.

Radiology. 2016 Dec;281(3):907-918. Epub 2016 Sep 16.

PMID:
27636026
8.

The RING 2.0 web server for high quality residue interaction networks.

Piovesan D, Minervini G, Tosatto SC.

Nucleic Acids Res. 2016 Jul 8;44(W1):W367-74. doi: 10.1093/nar/gkw315. Epub 2016 May 19.

9.

Knowledge-Based Methods To Train and Optimize Virtual Screening Ensembles.

Swift RV, Jusoh SA, Offutt TL, Li ES, Amaro RE.

J Chem Inf Model. 2016 May 23;56(5):830-42. doi: 10.1021/acs.jcim.5b00684. Epub 2016 May 3.

10.

Enhanced Prediction and Characterization of CDK Inhibitors Using Optimal Class Distribution.

Nath A, Karthikeyan S.

Interdiscip Sci. 2017 Jun;9(2):292-303. doi: 10.1007/s12539-016-0151-1. Epub 2016 Feb 15.

PMID:
26879961
11.

Consensus models for CDK5 inhibitors in silico and their application to inhibitor discovery.

Fang J, Yang R, Gao L, Yang S, Pang X, Li C, He Y, Liu AL, Du GH.

Mol Divers. 2015 Feb;19(1):149-62. doi: 10.1007/s11030-014-9561-3. Epub 2014 Dec 16.

PMID:
25511641
12.

Nonlinear scoring functions for similarity-based ligand docking and binding affinity prediction.

Brylinski M.

J Chem Inf Model. 2013 Nov 25;53(11):3097-112. doi: 10.1021/ci400510e. Epub 2013 Nov 11.

PMID:
24171431
13.

Machine learning methods for prediction of CDK-inhibitors.

Ramana J, Gupta D.

PLoS One. 2010 Oct 13;5(10):e13357. doi: 10.1371/journal.pone.0013357.

14.

Robust optimization of scoring functions for a target class.

Seifert MH.

J Comput Aided Mol Des. 2009 Sep;23(9):633-44. doi: 10.1007/s10822-009-9276-1. Epub 2009 May 27.

PMID:
19471858
15.

Feature-map vectors: a new class of informative descriptors for computational drug discovery.

Landrum GA, Penzotti JE, Putta S.

J Comput Aided Mol Des. 2006 Dec;20(12):751-62. Epub 2007 Jan 5.

PMID:
17205374
16.

Robust diagnosis of non-Hodgkin lymphoma phenotypes validated on gene expression data from different laboratories.

Bhanot G, Alexe G, Levine AJ, Stolovitzky G.

Genome Inform. 2005;16(1):233-44.

PMID:
16362926
17.

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