PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Global modeling of transcriptional responses in interaction networks
Leo Lahti, Juha Knuuttila and Samuel Kaski
Bioinformatics Volume 26, pp. 2713-2720, 2010.


Motivation: Cell-biological processes are regulated through a complex network of interactions between genes and their products. The processes, their activating conditions, and the associated transcriptional responses are often unknown. Organism-wide modeling of network activation can reveal unique and shared mechanisms between tissues, and potentially as yet unknown processes. The same method can also be applied to cell-biological conditions in one or more tissues. Results: We introduce a novel approach for organism-wide discovery and analysis of transcriptional responses in interaction networks. The method searches for local, connected regions in a network that exhibit coordinated transcriptional response in a subset of tissues. Known interactions between genes are used to limit the search space and to guide the analysis. Validation on a human pathway network reveals physiologically coherent responses, functional relatedness between tissues, and coordinated, context-specific regulation of the genes. Availability: Implementation is freely available in R and Matlab at

EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
ID Code:7592
Deposited By:Samuel Kaski
Deposited On:17 March 2011