Sample Sidebar Module

This is a sample module published to the sidebar_top position, using the -sidebar module class suffix. There is also a sidebar_bottom position below the menu.

Sample Sidebar Module

This is a sample module published to the sidebar_bottom position, using the -sidebar module class suffix. There is also a sidebar_top position below the search.
قسم الحاسبات

Qusay Z. Abdullah*    &       Bara'a Ali Attea

Department of Computer Science, College of Science, Baghdad University, Baghdad, Iraq.

Abstract

Many complex real world systems in almost every discipline of biology, sociology, and engineering can be represented as graphs, or networks.Protein-protein interactions (PPI) network of a given organism is normally structured as groups of interacting and separable modules. One of the most interested problems that recently draw many research investigations in PPI networks is complex detection problem. Detecting natural divisions in such complex networks is proved to be extremely NP-hard problem wherein, recently, many research interests are devoted towards unraveling natural divisions in such PPI networks. Due to problem complexity, the field of Evolutionary Algorithms(EAs)revealspositive results; however, they lack the introduction of some problemspecific heuristic operators that can positively improve the predictive power of EA modelThe major contribution of this paper is to propose a heuristic operator to enable the EA to improve its searching ability for intra and inter interactions. One of the prominent EA models existing in literature (known as conductance) is adopted to inter-play with the proposed heuristic operator inside the EA general framework. One of the well known PPI networks (SaccaromycaesCerevisiae yeast PPI network) and one reference set of benchmark complexes created from MIPS are used in the experiments. The results prove the positive impact of the proposed heuristic operator to harness the strength of the EA model.