Developmental Trend Derived from Modules of Wnt Signaling Pathways Losiana Nayak and Rajat K. De Machine Intelligence Unit, Indian Statistical Institute 203 B. T. Road, Kolkata - 700108, India {losiana t,rajat}@isical.ac.in http://www.isical.ac.in/~{losiana_t,rajat} Abstract. In this paper, we deal with the idea of creating a devel- opmental trend from Wnt signaling pathways of different species. Wnt signaling pathway is involved in many crucial biological processes in- cluding from early embryonic development to stem cell management at later stages. The pathway varies in topology and size for each species that gets reflected in its modules. A comparison among species-specific pathways, taking into account the modules and pathway structure (in terms of nodes and edges) will throw light on crucial turning points in the development of Wnt signaling pathway. Hence, 31 species-specific Wnt signaling pathways have been modularized by the Modularization algorithm already developed by the authors. The modules were com- pared among themselves to find the trend of development. The trend established conserved modules among these pathways. Keywords: Modularization algorithm, Evolution, Phylogenetic tree construction, Computational Phylogenetics. 1 Introduction In biological terms, a signal transduction pathway, is a set of established genes and related factors, which operate in synchronous manner to create cascades of reactions, ultimately generating a response to stimuli in vivo. From graph theo- retical point of view, these genes and related factors can be considered as nodes and the interactions among them as edges of a network. A pathway conceived in such a way is open to all kind of network analysis paradigms. Network compar- ison (by alignment) to uncover biological functions and phylogeny [1] is one of them. Networks derived from biological pathways (gene regulatory, metabolic, signal transduction, protein-protein interaction networks) can be aligned by size of the network, sequence similarity of the genes/proteins, functional similarity of the enzymes/proteins and presence of common topological structures (graphlets) among others. One or all of these factors are considered while creating a tree from a set of biological networks. In addition to such factors, we add another factor named ‘modules’ [2]. Modules throw light on operational sophistication of a network. It is dependent on two other parameters, viz., size (nodes) and topology (interactions). A tree generated by taking these three linked parame- ters can shed enough light on subtle changes of the network among the species, S.O. Kuznetsov et al. (Eds.): PReMI 2011, LNCS 6744, pp. 400–405, 2011. c  Springer-Verlag Berlin Heidelberg 2011