An analysis pipeline for the inference of protein-protein interaction networks

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 dat...

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Bibliographic Details
Published inInternational journal of data mining and bioinformatics Vol. 3; no. 4; p. 409
Main Authors Taylor, Ronald C, Singhal, Mudita, Daly, Don S, Gilmore, Jason, Cannon, William R, Domico, Kelly, White, Amanda M, Auberry, Deanna L, Auberry, Kenneth J, Hooker, Brian S, Hurst, Greg, McDermott, Jason E, McDonald, W Hayes, Pelletier, Dale A, Schmoyer, Denise, Wiley, H Steven
Format Journal Article
LanguageEnglish
Published Switzerland 01.01.2009
Subjects
Algorithms
Computational Biology - methods
Databases, Protein
Mass Spectrometry
Protein Interaction Mapping - methods
Proteins - chemistry
Proteins - metabolism
Software
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ISSN1748-5673
DOI10.1504/IJDMB.2009.029204

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Summary: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.
ISSN:1748-5673
DOI:10.1504/IJDMB.2009.029204