NDLI: Large-scale models of signal propagation in human cells derived from discovery phosphoproteomic data

Content Provider	PubMed Central
Author	Terfve, Camille D. A. Wilkes, Edmund H. Casado, Pedro Cutillas, Pedro R. Julio, Saez-rodriguez
Copyright Year	2015
Abstract	Mass spectrometry is widely used to probe the proteome and its modifications in an untargeted manner, with unrivalled coverage. Applied to phosphoproteomics, it has tremendous potential to interrogate phospho-signalling and its therapeutic implications. However, this task is complicated by issues of undersampling of the phosphoproteome and challenges stemming from its high-content but low-sample-throughput nature. Hence, methods using such data to reconstruct signalling networks have been limited to restricted data sets and insights (for example, groups of kinases likely to be active in a sample). We propose a new method to handle high-content discovery phosphoproteomics data on perturbation by putting it in the context of kinase/phosphatase-substrate knowledge, from which we derive and train logic models. We show, on a data set obtained through perturbations of cancer cells with small-molecule inhibitors, that this method can study the targets and effects of kinase inhibitors, and reconcile insights obtained from multiple data sets, a common issue with these data.
Related Links	http://dx.doi.org/10.1038/ncomms9033
Starting Page	8033
File Format	PDF
ISSN	20411723
e-ISSN	20411723
Journal	Nature Communications
Volume Number	6
Language	English
Publisher	Nature Pub. Group
Publisher Date	2015-09-01
Access Restriction	Open
Rights Holder	Nature Pub. Group
Subject Keyword	Biochemistry, Genetics and Molecular Biology(all) Physics and Astronomy(all) Chemistry(all) Research in Higher Education
Content Type	Text
Resource Type	Article
Subject	Chemistry Physics and Astronomy Biochemistry, Genetics and Molecular Biology

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