The rise in computational systems biology approaches for understanding NF-κB signaling dynamics

Richard A Williams; Jon Timmis; Eva E Qwarnstrom

doi:10.1126/scisignal.aac6503

The rise in computational systems biology approaches for understanding NF-κB signaling dynamics

Sci Signal. 2015 Jul 14;8(385):fs13. doi: 10.1126/scisignal.aac6503.

Authors

Richard A Williams¹, Jon Timmis², Eva E Qwarnstrom³

Affiliations

¹ Simulation Group, Department of Management Science, Lancaster University, Lancaster LA1 4YX, UK. r.williams4@lancaster.ac.uk.
² Department of Electronics, University of York, Heslington, York YO10 5DD, UK. York Computational Immunology Laboratory, University of York, Heslington, York YO10 5DD, UK.
³ Department of Cardiovascular Science, Sheffield University Medical School, Sheffield S10 2RX, UK. Department of Pathology, University of Washington, Seattle, WA 98195, USA.

PMID: 26175491
DOI: 10.1126/scisignal.aac6503

Abstract

A study by Cheng et al. in this issue of Science Signaling highlights the distinct single-cell signaling characteristics conferred by pathways mediated by the adaptor proteins MyD88 and TRIF in the TLR4-dependent activation of the transcription factor nuclear factor κB (NF-κB).

Publication types

Research Support, Non-U.S. Gov't
Comment

MeSH terms

Adaptor Proteins, Vesicular Transport / metabolism*
Animals
Myeloid Differentiation Factor 88 / metabolism*
Signal Transduction / physiology*
Toll-Like Receptor 4 / metabolism*

Substances

Adaptor Proteins, Vesicular Transport
Myeloid Differentiation Factor 88
Toll-Like Receptor 4

Abstract

Publication types

MeSH terms

Substances

Grants and funding