الفهرس | Only 14 pages are availabe for public view |
Abstract Discovering Protein-Protein Interactions (PPI) is an area of active research in computational biology. Identifying interactions among proteins was shown to help discover new drugs and prevent many diseases. The interactions between HIV -1 proteins and Human proteins is a particular PPI problem which study might lead to the discovery of important interactions responsible for Acquired Immune Deficiency Syndrome (AIDS) .This thesis presents an algorithm that applies the data mining for extracting hierarchical bi- clusters and minimal covers of PPI without losing information. The COARMN algorithm is based on the frequent closed item sets framework to efficiently generate a hierarchy of conceptual clusters and non-redundant sets of association rules with supporting object lists to integrate additional information about proteins. Experimental results show that the COARMN algorithm is more accurate than |