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Items: 1 to 20 of 98

1.

Kinome Render: a stand-alone and web-accessible tool to annotate the human protein kinome tree.

Chartier M, Chénard T, Barker J, Najmanovich R.

PeerJ. 2013 Aug 8;1:e126. doi: 10.7717/peerj.126. Print 2013.

2.

KinMap: a web-based tool for interactive navigation through human kinome data.

Eid S, Turk S, Volkamer A, Rippmann F, Fulle S.

BMC Bioinformatics. 2017 Jan 5;18(1):16. doi: 10.1186/s12859-016-1433-7.

3.

PIIKA 2: an expanded, web-based platform for analysis of kinome microarray data.

Trost B, Kindrachuk J, Määttänen P, Napper S, Kusalik A.

PLoS One. 2013 Nov 29;8(11):e80837. doi: 10.1371/journal.pone.0080837. eCollection 2013.

4.
5.

Mapping of inhibitors and activity data to the human kinome and exploring promiscuity from a ligand and target perspective.

Hu Y, Kunimoto R, Bajorath J.

Chem Biol Drug Des. 2017 Jun;89(6):834-845. doi: 10.1111/cbdd.12919. Epub 2017 Jan 30.

PMID:
27933727
6.

Large-scale proteomics analysis of the human kinome.

Oppermann FS, Gnad F, Olsen JV, Hornberger R, Greff Z, Kéri G, Mann M, Daub H.

Mol Cell Proteomics. 2009 Jul;8(7):1751-64. doi: 10.1074/mcp.M800588-MCP200. Epub 2009 Apr 15.

7.
8.

PhyD3: a phylogenetic tree viewer with extended phyloXML support for functional genomics data visualization.

Kreft L, Botzki A, Coppens F, Vandepoele K, Van Bel M.

Bioinformatics. 2017 May 19. doi: 10.1093/bioinformatics/btx324. [Epub ahead of print]

PMID:
28525531
9.

Macromolecular crowding: chemistry and physics meet biology (Ascona, Switzerland, 10-14 June 2012).

Foffi G, Pastore A, Piazza F, Temussi PA.

Phys Biol. 2013 Aug 2;10(4):040301. [Epub ahead of print]

PMID:
23912807
10.

The human kinome and kinase inhibition.

Duong-Ly KC, Peterson JR.

Curr Protoc Pharmacol. 2013 Mar;Chapter 2:Unit2.9. doi: 10.1002/0471141755.ph0209s60.

11.

Kinannote, a computer program to identify and classify members of the eukaryotic protein kinase superfamily.

Goldberg JM, Griggs AD, Smith JL, Haas BJ, Wortman JR, Zeng Q.

Bioinformatics. 2013 Oct 1;29(19):2387-94. doi: 10.1093/bioinformatics/btt419. Epub 2013 Jul 31.

12.
13.

Presence and utility of intrinsically disordered regions in kinases.

Kathiriya JJ, Pathak RR, Clayman E, Xue B, Uversky VN, Davé V.

Mol Biosyst. 2014 Nov;10(11):2876-88. doi: 10.1039/c4mb00224e.

PMID:
25099472
14.

Kinase inhibition-related adverse events predicted from in vitro kinome and clinical trial data.

Yang X, Huang Y, Crowson M, Li J, Maitland ML, Lussier YA.

J Biomed Inform. 2010 Jun;43(3):376-84. doi: 10.1016/j.jbi.2010.04.006. Epub 2010 May 1.

15.

Structure-guided selection of specificity determining positions in the human Kinome.

Moll M, Finn PW, Kavraki LE.

BMC Genomics. 2016 Aug 18;17 Suppl 4:431. doi: 10.1186/s12864-016-2790-3.

16.

Taxonomic colouring of phylogenetic trees of protein sequences.

Palidwor G, Reynaud EG, Andrade-Navarro MA.

BMC Bioinformatics. 2006 Feb 17;7:79.

17.

A targeted quantitative proteomics strategy for global kinome profiling of cancer cells and tissues.

Xiao Y, Guo L, Wang Y.

Mol Cell Proteomics. 2014 Apr;13(4):1065-75. doi: 10.1074/mcp.M113.036905. Epub 2014 Feb 11.

18.

SCOWLP: a web-based database for detailed characterization and visualization of protein interfaces.

Teyra J, Doms A, Schroeder M, Pisabarro MT.

BMC Bioinformatics. 2006 Mar 2;7:104.

19.

Integrative analysis of high-throughput RNAi screen data identifies the FER and CRKL tyrosine kinases as new regulators of the mitogenic ERK-dependent pathways in transformed cells.

Nizard P, Ezan F, Bonnier D, Le Meur N, Langouët S, Baffet G, Arlot-Bonnemains Y, Théret N.

BMC Genomics. 2014 Dec 23;15:1169. doi: 10.1186/1471-2164-15-1169.

20.

The sea urchin kinome: a first look.

Bradham CA, Foltz KR, Beane WS, Arnone MI, Rizzo F, Coffman JA, Mushegian A, Goel M, Morales J, Geneviere AM, Lapraz F, Robertson AJ, Kelkar H, Loza-Coll M, Townley IK, Raisch M, Roux MM, Lepage T, Gache C, McClay DR, Manning G.

Dev Biol. 2006 Dec 1;300(1):180-93. Epub 2006 Sep 12.

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