TY - JOUR

T1 - RAIN

T2 - RNA-protein Association and Interaction Networks

AU - Junge, Alexander

AU - Refsgaard, Jan C

AU - Garde, Christian

AU - Pan, Xiaoyong

AU - Santos, Alberto

AU - Alkan, Ferhat

AU - Anthon, Christian

AU - von Mering, Christian

AU - Workman, Christopher T

AU - Jensen, Lars Juhl

AU - Gorodkin, Jan

N1 - © The Author(s) 2017. Published by Oxford University Press.

PY - 2017

Y1 - 2017

N2 - 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: https://rth.dk/resources/rain.

AB - 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: https://rth.dk/resources/rain.

U2 - 10.1093/database/baw167

DO - 10.1093/database/baw167

M3 - Journal article

C2 - 28077569

VL - 2017

JO - Database : the journal of biological databases and curation

JF - Database : the journal of biological databases and curation

SN - 1758-0463

M1 - baw167

ER -