TY - GEN
T1 - NetceRNA
T2 - 2013 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2013
AU - Flores, Mario
AU - Huang, Yufei
AU - Chen, Yidong
N1 - Copyright:
Copyright 2014 Elsevier B.V., All rights reserved.
PY - 2013
Y1 - 2013
N2 - By using the competing endogenous RNA (ceRNA) concept, we implemented a web-based application TraceRNA. TraceRNA allows us to interactively construct a regulation network for a specific phenotype by using a disease-specific transcriptome data. In this work, we further extend the TraceRNA with a novel algorithm implementation where we examined the microRNA expression derived from same disease type. The proposed algorithm, NetceRNA, finds an optimized network representation under a certain phenotype context by iteratively perturbing the network and measuring the network configuration change with respect to the original ceRNA network. The resulting algorithm outputs an improved network together with a ranked list of genes and miRNAs which are characteristic of the specific phenotype. To illustrate the utility of NetceRNA, gene expression and microRNA expression data of breast cancer study from The Cancer Genome Atlas (TCGA) were used.
AB - By using the competing endogenous RNA (ceRNA) concept, we implemented a web-based application TraceRNA. TraceRNA allows us to interactively construct a regulation network for a specific phenotype by using a disease-specific transcriptome data. In this work, we further extend the TraceRNA with a novel algorithm implementation where we examined the microRNA expression derived from same disease type. The proposed algorithm, NetceRNA, finds an optimized network representation under a certain phenotype context by iteratively perturbing the network and measuring the network configuration change with respect to the original ceRNA network. The resulting algorithm outputs an improved network together with a ranked list of genes and miRNAs which are characteristic of the specific phenotype. To illustrate the utility of NetceRNA, gene expression and microRNA expression data of breast cancer study from The Cancer Genome Atlas (TCGA) were used.
KW - ceRNAs
KW - gene regulatory network
KW - microRNAs
UR - http://www.scopus.com/inward/record.url?scp=84897689802&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84897689802&partnerID=8YFLogxK
U2 - 10.1109/GENSIPS.2013.6735921
DO - 10.1109/GENSIPS.2013.6735921
M3 - Conference contribution
AN - SCOPUS:84897689802
SN - 9781479934621
T3 - Proceedings - IEEE International Workshop on Genomic Signal Processing and Statistics
SP - 24
EP - 27
BT - 2013 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2013 - Proceedings
Y2 - 17 November 2013 through 19 November 2013
ER -