HIGHLIGHTS Outline of EGF dependent in-vivo phosphotyrosine signaling in lung tissue A peptide based screen identifies proteins recruited to regulated phosphotyrosine sites in lung tissue Several somatic mutations affect proline residues within position +3 of regulated phosphotyrosine sites and introduce molecular switches A lung cancer oncogenic mutation in EGFR causes aberrant activation of phosphorylation signaling pathways by switching of a recruited protein complex Cancer mutations in vicinity of phosphotyrosine sites induce molecular switches that alter protein signaling networks Introduction of cutting-edge LC-MS instrumentation and DIA enables scalable, rapid and highthroughput analysis of phosphotyrosine site interactions
Protein association networks can be inferred from a range of resources including
experimental data, literature mining and computational predictions. These types of
evidence are emerging for non-coding RNAs (ncRNAs) as well. However, integration of
ncRNAs into protein association networks is challenging due to data heterogeneity.
Here, we present a database of ncRNA–RNA and ncRNA–protein
interactions and its integration with the STRING database of protein–protein
interactions. These ncRNA associations cover four organisms and have been established
from curated examples, experimental data, interaction predictions and automatic
literature mining. RAIN uses an integrative scoring scheme to assign a confidence
score to each interaction. We demonstrate that RAIN outperforms the underlying
microRNA-target predictions in inferring ncRNA interactions. RAIN can be operated
through an easily accessible web interface and all interaction data can be
downloaded.Database URL:
http://rth.dk/resources/rain
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