TY - JOUR
T1 - ResponseNet v.3
T2 - revealing signaling and regulatory pathways connecting your proteins and genes across human tissues
AU - Basha, Omer
AU - Mauer, Omry
AU - Simonovsky, Eyal
AU - Shpringer, Rotem
AU - Yeger-Lotem, Esti
N1 - Funding Information: This work and the open access charge were funded by the Broad Institute and the Israel Science Foundation [2435/16 to E.Y-L]. Conflict of interest statement. None declared. Publisher Copyright: © 2019 The Author(s).
PY - 2019/7/1
Y1 - 2019/7/1
N2 - ResponseNet v.3 is an enhanced version of ResponseNet, a web server that is designed to highlight signaling and regulatory pathways connecting user-defined proteins and genes by using the ResponseNet network optimization approach (http://netbio.bgu.ac.il/respnet). Users run ResponseNet by defining source and target sets of proteins, genes and/or microRNAs, and by specifying a molecular interaction network (interactome). The output of ResponseNet is a sparse, high-probability interactome subnetwork that connects the two sets, thereby revealing additional molecules and interactions that are involved in the studied condition. In recent years, massive efforts were invested in profiling the transcriptomes of human tissues, enabling the inference of human tissue interactomes. ResponseNet v.3 expands ResponseNet2.0 by harnessing ∼11,600 RNA-sequenced human tissue profiles made available by the Genotype-Tissue Expression consortium, to support context-specific analysis of 44 human tissues. Thus, ResponseNet v.3 allows users to illuminate the signaling and regulatory pathways potentially active in the context of a specific tissue, and to compare them with active pathways in other tissues. In the era of precision medicine, such analyses open the door for tissue- and patient-specific analyses of pathways and diseases.
AB - ResponseNet v.3 is an enhanced version of ResponseNet, a web server that is designed to highlight signaling and regulatory pathways connecting user-defined proteins and genes by using the ResponseNet network optimization approach (http://netbio.bgu.ac.il/respnet). Users run ResponseNet by defining source and target sets of proteins, genes and/or microRNAs, and by specifying a molecular interaction network (interactome). The output of ResponseNet is a sparse, high-probability interactome subnetwork that connects the two sets, thereby revealing additional molecules and interactions that are involved in the studied condition. In recent years, massive efforts were invested in profiling the transcriptomes of human tissues, enabling the inference of human tissue interactomes. ResponseNet v.3 expands ResponseNet2.0 by harnessing ∼11,600 RNA-sequenced human tissue profiles made available by the Genotype-Tissue Expression consortium, to support context-specific analysis of 44 human tissues. Thus, ResponseNet v.3 allows users to illuminate the signaling and regulatory pathways potentially active in the context of a specific tissue, and to compare them with active pathways in other tissues. In the era of precision medicine, such analyses open the door for tissue- and patient-specific analyses of pathways and diseases.
UR - http://www.scopus.com/inward/record.url?scp=85069236640&partnerID=8YFLogxK
U2 - https://doi.org/10.1093/nar/gkz421
DO - https://doi.org/10.1093/nar/gkz421
M3 - Article
C2 - 31114913
SN - 0305-1048
VL - 47
SP - W242-W247
JO - Nucleic acids research
JF - Nucleic acids research
IS - W1
ER -
