Inference of Predictive Phospho-regulatory Networks from LC-MS/MS Phosphoproteomics Data

Sebastian Vlaic, Robert Altwasser, Peter Kupfer, Carol L. Nilsson, Mark Emmett, Anke Meyer-Baese, Reinhard Guthke

2016

Abstract

In the field of transcriptomics data the automated inference of predictive gene regulatory networks from high-throughput data is a common approach for the identification of novel genes with potential therapeutic value. Sophisticated methods have been developed that extensively make use of diverse sources of prior-knowledge to obtain biologically relevant hypotheses. Transferring such concepts to the field of phosphoproteomics data has the potential to reveal new insights into phosphorylation-related signaling mechanisms. In this study we conceptually adapt the TILAR network inference algorithm for the inference of a phospho-regulatory network. Therefore, we use published phosphoproteomics data of WP1193 treated and IL6-stimulated glioblastoma stem cells under normoxic and hypoxic condition. Peptides corresponding to 21 differentially phosphorylated proteins were used for network inference. Topological analysis of the phospho-regulatory network suggests lamin B2 (LMNB2) and spectrin, beta, non-erythrocytic 1 (SPTBN1) as potential hub-proteins associated with the alteration of phosphorylation under the observed conditions. Altogether, our results show that inference of phospho-regulatory networks can aid in the understanding of complex molecular mechanisms and cellular processes of biological systems.

Paper Citation

in Harvard Style

Vlaic S., Altwasser R., Kupfer P., Nilsson C., Emmett M., Meyer-Baese A. and Guthke R. (2016). Inference of Predictive Phospho-regulatory Networks from LC-MS/MS Phosphoproteomics Data . In Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOINFORMATICS, (BIOSTEC 2016) ISBN 978-989-758-170-0, pages 85-91. DOI: 10.5220/0005743000850091

in Bibtex Style

@conference{bioinformatics16,
author={Sebastian Vlaic and Robert Altwasser and Peter Kupfer and Carol L. Nilsson and Mark Emmett and Anke Meyer-Baese and Reinhard Guthke},
title={Inference of Predictive Phospho-regulatory Networks from LC-MS/MS Phosphoproteomics Data},
booktitle={Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOINFORMATICS, (BIOSTEC 2016)},
year={2016},
pages={85-91},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005743000850091},
isbn={978-989-758-170-0},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOINFORMATICS, (BIOSTEC 2016)
TI - Inference of Predictive Phospho-regulatory Networks from LC-MS/MS Phosphoproteomics Data
SN - 978-989-758-170-0
AU - Vlaic S.
AU - Altwasser R.
AU - Kupfer P.
AU - Nilsson C.
AU - Emmett M.
AU - Meyer-Baese A.
AU - Guthke R.
PY - 2016
SP - 85
EP - 91
DO - 10.5220/0005743000850091