Title :
SEBINI-CABIN: An Analysis Pipeline for Biological Network Inference, with a Case Study in Protein-Protein Interaction Network Reconstruction
Author :
Taylor, Ronald C. ; Singhal, Mudita ; Daly, Don S. ; Domico, Kelly ; White, Amanda M. ; Auberry, Deanna L. ; Auberry, Kenneth J. ; Hooker, Brian ; Hurst, Greg ; McDermott, Jason ; McDonald, W. Hayes ; Pelletier, Dale ; Schmoyer, Denise ; Cannon, William R
Author_Institution :
Pacific Northwest Nat. Lab., Richland
Abstract :
The Software Environment for Biological Network Inference (SEBINI) has been created to provide an interactive environment for the deployment and testing of network inference algorithms that use high-throughput expression data. Networks inferred from the SEBINI software platform can be further analyzed using the Collective Analysis of Biological Interaction Networks (CABIN), software that allows integration and analysis of protein- protein interaction and gene-to-gene regulatory evidence obtained from multiple sources. In this paper, we present a case study on the SEBINI and CABIN tools for protein-protein interaction network reconstruction. Incorporating the Bayesian Estimator of Protein-Protein Association Probabilities (BEPro) algorithm into the SEBINI toolkit, we have created a pipeline for structural inference and supplemental analysis of protein- protein interaction networks from sets of mass spectrometry bait-prey experiment data.
Keywords :
Bayes methods; biology computing; genetics; inference mechanisms; proteins; Byesian Estimator of Protein-Protein Association Probabilities algorithm; Collective Analysis of Biological Interaction Networks; SEBINI software platform; SEBINI toolkit; SEBINI-CABIN; Software Environment for Biological Network Inference; biological network inference; gene-to-gene regulatory evidence; mass spectrometry bait-prey experiment; network inference algorithms; protein-protein interaction network reconstruction; Algorithm design and analysis; Bayesian methods; Bioinformatics; Biological interactions; Inference algorithms; Mass spectroscopy; Pipelines; Proteins; Software algorithms; Software tools;
Conference_Titel :
Machine Learning and Applications, 2007. ICMLA 2007. Sixth International Conference on
Conference_Location :
Cincinnati, OH
Print_ISBN :
978-0-7695-3069-7
DOI :
10.1109/ICMLA.2007.63