An analysis pipeline for the inference of protein-protein interaction networks. (11th November 2009)

• Record Type: Journal Article
• Authors: Taylor, Ronald C.; Singhal, Mudita; Daly, Don S.; Gilmore, Jason; Cannon, William; Domico, Kelly; White, Amanda; Auberry, Deanna; Auberry, Kenneth; Hooker, Brian; Hurst, Greg; McDermott, Jason; McDonald, W.; Pelletier, Dale; Schmoyer, Denise; Wiley, H.
• Is Part Of: International journal of data mining and bioinformatics. Volume 3:Number 4(2009)
• Page Start: 409
• Page End: 430
• Publication Date: 2009-11-11
• Subjects: network inference pipeline -- protein-protein interactions -- biological networks -- mass spectrometry -- Bayesian estimator -- bait-prey data -- bioinformatics -- protein-protein associations -- structured workflow; Data mining -- Periodicals; Bioinformatics -- Periodicals; 006.312
• Languages: English
• ISSNs: 1748-5673

Abstract

We present a platform for the reconstruction of protein-protein interaction networks inferred from Mass Spectrometry (MS) bait-prey data. The Software Environment for Biological Network Inference (SEBINI), an environment for the deployment of network inference algorithms that use high-throughput data, forms the platform core. Among the many algorithms available in SEBINI is the Bayesian Estimator of Probabilities of Protein-Protein Associations (BEPro3) algorithm, which is used to infer interaction networks from such MS affinity isolation data. Also, the pipeline incorporates the Collective Analysis of Biological Interaction Networks (CABIN) software. We have thus created a structured workflow for protein-protein network inference and supplemental analysis.