Background Genomic, high-throughput and proteomic gene expression data, when integrated, can be used to map the interaction networks between genes and proteins. topological distribution. The constituent biological phenomena are explored through the use of the Gene Ontology. We thus construct a network of networks, and demonstrate that both proteins and gene relationship systems are modular in character. By concentrating on the ontological classification, we’re able to determine the complete GO information that are distributed at different degrees of hierarchy. Within each submodule a lot of the protein are biologically correlated, and participate in groups of unique biological activities. Conclusions The LTBR antibody present approach is an effective method for discovering coherent gene modules and protein submodules. We show that this also provides a means of determining biological pathways (both novel and as well those that have been reported previously) that are related, in the present instance, to breast cancer. Comparable strategies are likely to be useful in the analysis of other diseases as well. approach to biological phenomena is usually that of networks and the interactions among them. BNP (1-32), human Improvements in genomic, proteomic and high-throughput gene expression data, when integrated, can be used to map the conversation BNP (1-32), human networks between genes and proteins, as well as their association with specific biological activities. It has also become increasingly obvious that an integrated analysis of these considerable components is crucial, especially in the case of cancers [1]. Mutation in biologically BNP (1-32), human correlated genes affects the translation of important proteins that do not function in isolation: unique biological activities are the result of the coordinated action of BNP (1-32), human multiple proteins [2] and a reduction in the synthesis of one protein can directly impact various specialized biological actions. In the case of breast malignancy for example, the conversation network of 6004 proteins is usually, in different combinations, associated with 5732 biological processes (BP), 1930 molecular functions (MF) and 879 cellular elements (CC) as given in the Gene Ontology Annotation (GOA) [3] data source. Upon this scale it really is tough to interpret the business process of such systems which may be composed of a large number of structural subunits. The greater connected subunits take part in multiple biological activities [4] extremely. The alternative strategy, splitting up the complicated network into many interacting sub-networks specifically, can be even more useful. These sub-networks help analyse the experience at various degrees of specificity, specifically in case there is complicated diseases where in fact the primary interest is certainly to elucidate the coordination process that handles the development of the condition. The modular character of a multitude of complicated systems has been investigated in detail in recent years, ranging from social networks [5], cellular phone networks [6], collaboration networks [7], citation networks [8], gene co-occurrence network [9], protein-protein connection (PPI) networks [10], and metabolic networks [10]. A module can be defined as a subset of the nodes such that nodes within the module are densely connected while becoming sparsely connected with nodes in additional modules [11]. Modules are the building blocks of higher-level practical organization, and may show hierarchical properties. In particular, modules can be recursively divided into smaller submodules; such submodules are a wealthy way to obtain information in natural systems [12-15] potentially. Nodes within a submodule will have got related natural properties carefully, and therefore separating a network into modules and submodules makes it possible to comprehend the more particular domains of activities where they participate, possibly or within a coordinated way singly. (By domains we mean right here the specializations described by Gene Ontology (Move) [16], bP namely,.