RAIN: RNA-protein Association and Interaction Networks
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RAIN : RNA-protein Association and Interaction Networks. / Junge, Alexander; Refsgaard, Jan C; Garde, Christian; Pan, Xiaoyong; Santos, Alberto; Alkan, Ferhat; Anthon, Christian; von Mering, Christian; Workman, Christopher T; Jensen, Lars Juhl; Gorodkin, Jan.
In: Database: The Journal of Biological Databases and Curation, Vol. 2017, baw167, 2017.Research output: Contribution to journal › Journal article › Research › peer-review
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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 -
ID: 172526314