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Systems-level insights into cellular regulation: inferring, analysing, and modelling intracellular

Summary: Systems-level insights into cellular regulation:
inferring, analysing, and modelling intracellular
C. Christensen, J. Thakar and R. Albert
Abstract: Genes and gene products interact on several levels, forming transcriptional regulatory-,
protein interaction-, metabolic- and signal transduction networks. Genetic, biochemical and mol-
ecular biology techniques have been used for decades to identify biological interactions; newly
developed high-throughput methods now allow for the construction of genome-level interaction
maps. In parallel, high-throughput expression data paired with computational algorithms can be
used to infer networks of interactions and causal relationships capable of producing the observed
experimental data. Graph-theoretical measures and network models are more and more frequently
used to discern functional and evolutionary constraints in the organisation of biological networks.
Perhaps most importantly, the combination of interaction and expression information allows the
formulation of quantitative and predictive dynamic models. Some of the dominant experimental
and computational methods used for the reconstruction or inference of cellular networks are
reviewed, also the biological insights that have been obtained from graph-theoretical analysis
of these networks, and the extension of static networks into various dynamic models capable of
providing a new layer of insight into the functioning of cellular systems is discussed.
1 Definition of cellular networks
A system of elements that interact or regulate each other can


Source: Albert, Réka - Departments of Biology & Physics, Pennsylvania State University


Collections: Biology and Medicine