Integrated network analysis platform for protein-protein interactions
By Jianmin Wu, T. Vallenius, K. Ovaska, J. Westermarck, T. Mäkelä, S. Hautaniemi. Nature Methods, 2009
337 citations recorded by the source corpus.
Subfields: Cell Biology, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/0d91cff8c20fa80ce6b2367aaa41261f663a5c36
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- Ruth Nussinov
- Celia Fontanillo
- Peter Csermely
- Huba J. M. Kiss
- Tamás Korcsmáros
- Sean M. Grimmond
- Gabor London
- J De Las Rivas
Citations in the corpus
- Structure and dynamics of molecular networks: A novel paradigm of drug discovery: A comprehensive review (2012, background): “…Combines protein–protein interaction and signaling data http://PathwayLinker.org Farkas et al., 2012 PINA Interactome analysis http://cbg.garvan.unsw.edu.au/pina Wu et al., 2009b; Cowley et al., 2012 PIPs Human protein–protein interaction prediction http://www.compbio.dundee.ac.uk/www-pips…”
- PINA v2.0: mining interactome modules (2011, background): “The first version of PINA (11) has established a non-redundant PPI database, updated quarterly based on the integration of protein interaction data from six publicly available, manually curated databases: IntAct (12), MINT (13), BioGRID (14), DIP (15), HPRD (16) and MIPS MPact (17).”
- Protein–Protein Interactions Essentials: Key Concepts to Building and Analyzing Interactome Networks (2010, background): “Regarding meta-databases, APID [23,24] and PINA [25] represent to date the most comprehensive efforts to integrate PPI experimental data in single platforms.”
- Genome-wide association study identifies five susceptibility loci for glioma (2009, methodology): “We searched for interactions between proteins encoded by genes mapping to association signals using the program PIN”
- Drug repositioning: a machine-learning approach through data integration (2013, methodology): “To cope with the scarce granularity of this measure, we also defined a finer dissimilarity measure KTAR based on on the PPI database [40,41] as follows.”