TY - GEN
T1 - Inferring weighted and directed gene interaction networks from gene expression data using the phi-mixing coefficient
AU - Singh, Nitin
AU - Ahsen, Mehmet Eren
AU - Mankala, Shiva
AU - Vidyasagar, M.
AU - White, Michael
PY - 2012
Y1 - 2012
N2 - In this paper, we present a new algorithm for reverse-engineering gene interaction networks (GINs) from expression data, using the so-called phi-mixing coefficient between two random variables. Unlike existing methods, the GINs constructed using the algorithm presented here have edges that are both directed and weighted. The GIN constructed is, in a very specific sense, a minimal network that is compatible with the data. Several GINs have been constructed for various data sets in lung cancer, ovarian cancer and melanoma. Lung cancer and melanoma networks have been validated by comparing their predictions against the output of ChIP-seq data. The neighbors of three transcription factors (ASCL1, PPARG and NKX2-1) in lung cancer, and one transcription factor SOX10 in melanoma, are significantly enriched with ChIP-seq genes compared to pure chance.
AB - In this paper, we present a new algorithm for reverse-engineering gene interaction networks (GINs) from expression data, using the so-called phi-mixing coefficient between two random variables. Unlike existing methods, the GINs constructed using the algorithm presented here have edges that are both directed and weighted. The GIN constructed is, in a very specific sense, a minimal network that is compatible with the data. Several GINs have been constructed for various data sets in lung cancer, ovarian cancer and melanoma. Lung cancer and melanoma networks have been validated by comparing their predictions against the output of ChIP-seq data. The neighbors of three transcription factors (ASCL1, PPARG and NKX2-1) in lung cancer, and one transcription factor SOX10 in melanoma, are significantly enriched with ChIP-seq genes compared to pure chance.
UR - http://www.scopus.com/inward/record.url?scp=84877841300&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84877841300&partnerID=8YFLogxK
U2 - 10.1109/GENSIPS.2012.6507755
DO - 10.1109/GENSIPS.2012.6507755
M3 - Conference contribution
AN - SCOPUS:84877841300
SN - 9781467352369
T3 - Proceedings - IEEE International Workshop on Genomic Signal Processing and Statistics
SP - 168
EP - 171
BT - Proceedings 2012 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2012
T2 - 2012 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2012
Y2 - 2 December 2012 through 4 December 2012
ER -