Nucleic Acids Research Advance Access originally published online on November 2, 2007
Nucleic Acids Research 2008 36(Database issue):D695-D699; doi:10.1093/nar/gkm902
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Nucleic Acids Research, 2008, Vol. 36, Database issue D695-D699
© 2007 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
This article appears in the following Nucleic Acids Research issue: Database issue [View the issue table of contents]
Articles |
NetworKIN: a resource for exploring cellular phosphorylation networks
1Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto, Canada, 2Center for Cancer Research, Massachusetts Institute of Technology, Cambridge, USA, 3The Institute of Cancer Research, London, UK, 4European Molecular Biology Laboratory, Heidelberg and 5Max-Delbrück-Centre for Molecular Medicine, Berlin, Germany
*To whom correspondence should be addressed. Tel: + 1 416 586 4800; Fax: + 1 416 586 8869; Email: linding{at}mshri.on.ca Correspondence may also be addressed to Tony Pawson. Tel: + 1 416 586 8262; Fax: + 1 416 586 8869; Email: pawson{at}mshri.on.ca
Received August 13, 2007. Revised October 3, 2007. Accepted October 4, 2007.
Protein kinases control cellular responses by phosphorylating specific substrates. Recent proteome-wide mapping of protein phosphorylation sites by mass spectrometry has discovered thousands of in vivo sites. Systematically assigning all 518 human kinases to all these sites is a challenging problem. The NetworKIN database (http://networkin.info) integrates consensus substrate motifs with context modelling for improved prediction of cellular kinase–substrate relations. Based on the latest human phosphoproteome from the Phospho.ELM and PhosphoSite databases, the resource offers insight into phosphorylation-modulated interaction networks. Here, we describe how NetworKIN can be used for both global and targeted molecular studies. Via the web interface users can query the database of precomputed kinase–substrate relations or obtain predictions on novel phosphoproteins. The database currently contains a predicted phosphorylation network with 20 224 site-specific interactions involving 3978 phosphoproteins and 73 human kinases from 20 families.
![]()
CiteULike
Connotea
Del.icio.us What's this?
This article has been cited by other articles:
![]() |
C.-C. Wu, S. Asgharzadeh, T. J. Triche, and D. Z. D'Argenio Prediction of human functional genetic networks from heterogeneous data using RVM-based ensemble learning Bioinformatics, March 15, 2010; 26(6): 807 - 813. [Abstract] [Full Text] [PDF] |
||||
![]() |
J. V. Olsen, M. Vermeulen, A. Santamaria, C. Kumar, M. L. Miller, L. J. Jensen, F. Gnad, J. Cox, T. S. Jensen, E. A. Nigg, et al. Quantitative Phosphoproteomics Reveals Widespread Full Phosphorylation Site Occupancy During Mitosis Sci. Signal., January 12, 2010; 3(104): ra3 - ra3. [Abstract] [Full Text] [PDF] |
||||
![]() |
J. Lin, Z. Xie, H. Zhu, and J. Qian Understanding protein phosphorylation on a systems level Briefings in Functional Genomics, January 7, 2010; (2010) elp045v1. [Abstract] [Full Text] [PDF] |
||||
![]() |
P. J. Boersema, L. Y. Foong, V. M. Y. Ding, S. Lemeer, B. van Breukelen, R. Philp, J. Boekhorst, B. Snel, J. den Hertog, A. B. H. Choo, et al. In-depth Qualitative and Quantitative Profiling of Tyrosine Phosphorylation Using a Combination of Phosphopeptide Immunoaffinity Purification and Stable Isotope Dimethyl Labeling Mol. Cell. Proteomics, January 1, 2010; 9(1): 84 - 99. [Abstract] [Full Text] [PDF] |
||||
![]() |
C. S. H. Tan, B. Bodenmiller, A. Pasculescu, M. Jovanovic, M. O. Hengartner, C. Jorgensen, G. D. Bader, R. Aebersold, T. Pawson, and R. Linding Comparative Analysis Reveals Conserved Protein Phosphorylation Networks Implicated in Multiple Diseases Sci. Signal., July 28, 2009; 2(81): ra39 - ra39. [Abstract] [Full Text] [PDF] |
||||
![]() |
N. Yachie, R. Saito, J. Sugahara, M. Tomita, and Y. Ishihama In Silico Analysis of Phosphoproteome Data Suggests a Rich-get-richer Process of Phosphosite Accumulation over Evolution Mol. Cell. Proteomics, May 1, 2009; 8(5): 1061 - 1071. [Abstract] [Full Text] [PDF] |
||||
![]() |
A. Lachmann and A. Ma'ayan KEA: kinase enrichment analysis Bioinformatics, March 1, 2009; 25(5): 684 - 686. [Abstract] [Full Text] [PDF] |
||||
![]() |
P. Kumar, B. C. Han, Z. Shi, J. Jia, Y. P. Wang, Y. T. Zhang, L. Liang, Q. F. Liu, Z. L. Ji, and Y. Z. Chen Update of KDBI: Kinetic Data of Bio-molecular Interaction database Nucleic Acids Res., January 1, 2009; 37(suppl_1): D636 - D641. [Abstract] [Full Text] [PDF] |
||||
![]() |
V. Navratil, B. de Chassey, L. Meyniel, S. Delmotte, C. Gautier, P. Andre, V. Lotteau, and C. Rabourdin-Combe VirHostNet: a knowledge base for the management and the analysis of proteome-wide virus-host interaction networks Nucleic Acids Res., January 1, 2009; 37(suppl_1): D661 - D668. [Abstract] [Full Text] [PDF] |
||||
![]() |
M. L. Miller, L. J. Jensen, F. Diella, C. Jorgensen, M. Tinti, L. Li, M. Hsiung, S. A. Parker, J. Bordeaux, T. Sicheritz-Ponten, et al. Linear Motif Atlas for Phosphorylation-Dependent Signaling Sci. Signal., September 2, 2008; 1(35): ra2 - ra2. [Abstract] [Full Text] [PDF] |
||||
![]() |
L. Li, C. Wu, H. Huang, K. Zhang, J. Gan, and S. S.-C. Li Prediction of phosphotyrosine signaling networks using a scoring matrix-assisted ligand identification approach Nucleic Acids Res., June 1, 2008; 36(10): 3263 - 3273. [Abstract] [Full Text] [PDF] |
||||




