NETWORKS, BIOLOGY AND SYSTEMS ENGINEERING: A CASE STUDY IN INFLAMMATION

Abstract

Biological systems can be modeled as networks of interacting components across multiple scales. A central problem in computational systems biology is to identify those critical components and the rules that define their interactions and give rise to the emergent behavior of a host response. In this paper we will discuss two fundamental problems related to the construction of transcription factor networks and the identification of networks of functional modules describing disease progression. We focus on inflammation as a key physiological response of clinical and translational importance.

Figure 1

(top) trivial overlapping bicluster definition. Although C defines a legitimate biclusters it should be eliminated; (bottom) Modeling the exclusion of trivial biclusters (Yang, Foteinou et al. 2007).

Figure 2

(top left) Identified biclusters; (top right) Infered interaction; (bottom) Network representations. More details are discussed in (Yang, Foteinou et al. 2007)

Figure 3

Deconvoluted interaction dynamics among the elements of the TF network, (Yang, Yarmush et al. 2009)

Figure 4

Notional modeling framework of LPS response. Upon binding to its receptor a signaling cascade is activated which leads to the up/down-regulation of numerous pro- and anti-inflammatory genes

Figure 5

A network of interacting components associated with the induction and control of the inflammatory response (Foteinou, Calvano et al. 2009; Foteinou, Calvano et al. 2009)

Figure 6

Dynamic profiles of the elements that constitute the physicochemical model of human inflammation (Foteinou, Calvano et al. 2009)

Figure 7

Model predictions of unresolved responses (Foteinou, Calvano et al. 2009)