TY - GEN
T1 - Inference of gene-regulatory networks using message-passing algorithms
AU - Shamaiah, Manohar
AU - Lee, Sang Hyun
AU - Vikalo, Haris
PY - 2010
Y1 - 2010
N2 - We present an application of message-passing techniques to gene regulatory network inference. The network inference is posed as a constrained linear regression problem, and solved by a distributed computationally efficient message-passing algorithm. Performance of the proposed algorithm is tested on gold standard data sets and evaluated using metrics provided by the DREAM2 challenge [1]Performance of the proposed algorithm is comparable to that of the techniques which yielded the best results in the DREAM2 challenge competition.
AB - We present an application of message-passing techniques to gene regulatory network inference. The network inference is posed as a constrained linear regression problem, and solved by a distributed computationally efficient message-passing algorithm. Performance of the proposed algorithm is tested on gold standard data sets and evaluated using metrics provided by the DREAM2 challenge [1]Performance of the proposed algorithm is comparable to that of the techniques which yielded the best results in the DREAM2 challenge competition.
KW - Gene regulatory networks
KW - L1-regularized model
KW - Message passing algorithms
UR - http://www.scopus.com/inward/record.url?scp=79952786532&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79952786532&partnerID=8YFLogxK
U2 - 10.1109/GENSIPS.2010.5719683
DO - 10.1109/GENSIPS.2010.5719683
M3 - Conference contribution
AN - SCOPUS:79952786532
SN - 9781612847924
T3 - 2010 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2010
BT - 2010 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2010
T2 - 2010 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2010
Y2 - 10 November 2010 through 12 November 2010
ER -