|An empirical framework for binary interactome mapping|
K Venkatesan, JF Rual, A Vazquez, U Stelzl, I Lemmens, ...
Nature methods 6 (1), 83-90, 2009
|HIPPIE: Integrating protein interaction networks with experiment based quality scores|
MH Schaefer, JF Fontaine, A Vinayagam, P Porras, EE Wanker, ...
PloS one 7 (2), e31826, 2012
|An integrative approach to ortholog prediction for disease-focused and other functional studies|
Y Hu, I Flockhart, A Vinayagam, C Bergwitz, B Berger, N Perrimon, ...
BMC bioinformatics 12 (1), 357, 2011
|A directed protein interaction network for investigating intracellular signal transduction|
A Vinayagam, U Stelzl, R Foulle, S Plassmann, M Zenkner, J Timm, ...
Science signaling 4 (189), rs8-rs8, 2011
|Controllability analysis of the directed human protein interaction network identifies disease genes and drug targets|
A Vinayagam, TE Gibson, HJ Lee, B Yilmazel, C Roesel, Y Hu, Y Kwon, ...
Proceedings of the National Academy of Sciences 113 (18), 4976-4981, 2016
|The Hippo signaling pathway interactome|
Y Kwon, A Vinayagam, X Sun, N Dephoure, SP Gygi, P Hong, N Perrimon
Science 342 (6159), 737-740, 2013
|Integrating protein-protein interaction networks with phenotypes reveals signs of interactions|
A Vinayagam, J Zirin, C Roesel, Y Hu, B Yilmazel, AA Samsonova, ...
Nature methods 11 (1), 94-99, 2014
|Applying support vector machines for gene ontology based gene function prediction|
A Vinayagam, R König, J Moormann, F Schubert, R Eils, KH Glatting, ...
BMC bioinformatics 5 (1), 116, 2004
|A regulatory network of Drosophila germline stem cell self-renewal|
D Yan, RA Neumüller, M Buckner, K Ayers, H Li, Y Hu, D Yang-Zhou, ...
Developmental cell 28 (4), 459-473, 2014
|Proteomic and functional genomic landscape of receptor tyrosine kinase and ras to extracellular signal–regulated kinase signaling|
AA Friedman, G Tucker, R Singh, D Yan, A Vinayagam, Y Hu, R Binari, ...
Science signaling 4 (196), rs10-rs10, 2011
|Protein complex–based analysis framework for high-throughput data sets|
A Vinayagam, Y Hu, M Kulkarni, C Roesel, R Sopko, SE Mohr, ...
Science signaling 6 (264), rs5-rs5, 2013
|Global gene expression profiling and cluster analysis in Xenopus laevis|
D Baldessari, Y Shin, O Krebs, R König, T Koide, A Vinayagam, U Fenger, ...
Mechanisms of development 122 (3), 441-475, 2005
|GOPET: a tool for automated predictions of Gene Ontology terms|
A Vinayagam, C del Val, F Schubert, R Eils, KH Glatting, S Suhai, R König
BMC bioinformatics 7 (1), 161, 2006
|Conserved regulators of nucleolar size revealed by global phenotypic analyses|
RA Neumüller, T Gross, AA Samsonova, A Vinayagam, M Buckner, ...
Science signaling 6 (289), ra70-ra70, 2013
|An integrative analysis of the InR/PI3K/Akt network identifies the dynamic response to insulin signaling|
A Vinayagam, MM Kulkarni, R Sopko, X Sun, Y Hu, A Nand, C Villalta, ...
Cell reports 16 (11), 3062-3074, 2016
|Combining genetic perturbations and proteomics to examine kinase-phosphatase networks in Drosophila embryos|
R Sopko, M Foos, A Vinayagam, B Zhai, R Binari, Y Hu, S Randklev, ...
Developmental cell 31 (1), 114-127, 2014
|DSDBASE: a consortium of native and modelled disulphide bonds in proteins|
A Vinayagam, G Pugalenthi, R Rajesh, R Sowdhamini
Nucleic acids research 32 (suppl_1), D200-D202, 2004
|A computational framework for boosting confidence in high-throughput protein-protein interaction datasets|
R Hosur, J Peng, A Vinayagam, U Stelzl, J Xu, N Perrimon, J Bienkowska, ...
Genome biology 13 (8), 1-14, 2012
|A rapid genome-wide microRNA screen identifies miR-14 as a modulator of Hedgehog signaling|
K Kim, A Vinayagam, N Perrimon
Cell reports 7 (6), 2066-2077, 2014
|Native and modeled disulfide bonds in proteins: Knowledge‐based approaches toward structure prediction of disulfide‐rich polypeptides|
RR Thangudu, A Vinayagam, G Pugalenthi, A Manonmani, B Offmann, ...
PROTEINS: Structure, Function, and Bioinformatics 58 (4), 866-879, 2005