Here we present most interesting recently published papers which used our tools for interpretation of experimental data to address important biological issues.
Proteomic analysis of dopamine and alfa-synuclein interplay in a cellular model of Parkinsons disease pathogenesis FEBS J. 2010 277(23):4909-19.
In this paper Alberio et al. this paper Alberio et al. used PPI spider to interpret data from a proteomic analysis of four sets of two-dimensional gels: proteomic investigation was conducted on control and alfa-synuclein overexpressing SH-SY5Y cells treated or not with dopamine. Experimentally identified proteins were analyzed in terms of both interaction network and GO classification enrichment using PPI spider. In both cases, bioinformatic analysis revealed that the NF-k-Betta pathway could be involved in determining the effects of dopamine treatment and alfa-synuclein overexpression. This allowed authors to experimentally validate the involvement of this transcription factor in the biological effects observed.
Proteomics in Parkinsons disease: An unbiased approach towards peripheral biomarkers and new therapies
Please see this review that stress the importance of network enrichment tools in the interpretation of proteomics data.
ATM-Dependent and -Independent Dynamics of the Nuclear Phosphoproteome After DNA Damage Science Signaling 3 (151).
In the paper, "ATM-Dependent and -Independent Dynamics of the Nuclear Phosphoproteome After DNA Damage" published recently in Science Signaling, Bensimon et al. used PPI spider to explore "Network organization of DNA damage-responsive proteins". The PPI Spider was used to connect 245 proteins from selected proteins into a network with a total of 386 nodes in which only one PPI Spider-added intermediate protein was allowed between two proteins from the input list. The authors conclude that "the addition of the 141 connecting proteins by PPI Spider had a marked impact on the significance of highly relevant GO terms. For example, the significance of RNA Splicing, DNA Binding, Regulation of Transcription, and daughter terms were increased by more than 10 orders of magnitude".