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

Ronald C. Taylor; Mudita Singhal; Don S. Daly; Jason G. Gilmore; William R. Cannon; Kelly Domico; Amanda White; Deanna L. Auberry; Kenneth J. Auberry; Brian S. Hooker; Greg Hurst; Jason E. McDermott; W. Hayes McDonald; Dale A. Pelletier; Denise Schmoyer; H. Steven Wiley

doi:10.1504/IJDMB.2009.029204

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

Ronald C. Taylor, Mudita Singhal, Don S. Daly, Jason G. Gilmore, William R. Cannon, Kelly Domico, Amanda White, Deanna L. Auberry, Kenneth J. Auberry, Brian S. Hooker, Greg Hurst, Jason E. McDermott, W. Hayes McDonald, Dale A. Pelletier, Denise Schmoyer, H. Steven Wiley

Integrative Microbiomics

Research output: Contribution to journal › Article › peer-review

3 Scopus citations

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. copyright

Original language	English
Pages (from-to)	409-430
Number of pages	22
Journal	International Journal of Data Mining and Bioinformatics
Volume	3
Issue number	4
DOIs	https://doi.org/10.1504/IJDMB.2009.029204
State	Published - 2009

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Taylor, R. C., Singhal, M., Daly, D. S., Gilmore, J. G., Cannon, W. R., Domico, K., White, A., Auberry, D. L., Auberry, K. J., Hooker, B. S., Hurst, G., McDermott, J. E., McDonald, W. H., Pelletier, D. A., Schmoyer, D., & Wiley, H. S. (2009). An analysis pipeline for the inference of protein-protein interaction networks. International Journal of Data Mining and Bioinformatics, 3(4), 409-430. https://doi.org/10.1504/IJDMB.2009.029204

@article{caea391e2bf74808a38346269cfc0bc2,

title = "An analysis pipeline for the inference of protein-protein interaction networks",

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. copyright",

author = "Taylor, {Ronald C.} and Mudita Singhal and Daly, {Don S.} and Gilmore, {Jason G.} and Cannon, {William R.} and Kelly Domico and Amanda White and Auberry, {Deanna L.} and Auberry, {Kenneth J.} and Hooker, {Brian S.} and Greg Hurst and McDermott, {Jason E.} and McDonald, {W. Hayes} and Pelletier, {Dale A.} and Denise Schmoyer and Wiley, {H. Steven}",

year = "2009",

doi = "10.1504/IJDMB.2009.029204",

language = "English",

volume = "3",

pages = "409--430",

journal = "International Journal of Data Mining and Bioinformatics",

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publisher = "Inderscience",

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Taylor, RC, Singhal, M, Daly, DS, Gilmore, JG, Cannon, WR, Domico, K, White, A, Auberry, DL, Auberry, KJ, Hooker, BS, Hurst, G, McDermott, JE, McDonald, WH, Pelletier, DA, Schmoyer, D & Wiley, HS 2009, 'An analysis pipeline for the inference of protein-protein interaction networks', International Journal of Data Mining and Bioinformatics, vol. 3, no. 4, pp. 409-430. https://doi.org/10.1504/IJDMB.2009.029204

TY - JOUR

T1 - An analysis pipeline for the inference of protein-protein interaction networks

AU - Taylor, Ronald C.

AU - Singhal, Mudita

AU - Daly, Don S.

AU - Gilmore, Jason G.

AU - Cannon, William R.

AU - Domico, Kelly

AU - White, Amanda

AU - Auberry, Deanna L.

AU - Auberry, Kenneth J.

AU - Hooker, Brian S.

AU - Hurst, Greg

AU - McDermott, Jason E.

AU - McDonald, W. Hayes

AU - Pelletier, Dale A.

AU - Schmoyer, Denise

AU - Wiley, H. Steven

PY - 2009

Y1 - 2009

N2 - 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. copyright

AB - 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. copyright

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SP - 409

EP - 430

JO - International Journal of Data Mining and Bioinformatics

JF - International Journal of Data Mining and Bioinformatics

IS - 4

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

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