Conversion of Imbalanced Data into A Stream Using SMOTE Algorithm

Abstract: Gene Ontology is structured as a directed acyclic graph, and each expression has distinct interaction to one or more other terms in the same domain and sometimes to other domains. High throughput techniques have become a primary approach to gathering biological data. These data can be used to explore relationships between genes and to identify disease. Clustering is a common methodology for the analysis of array data and many research laboratories are generating array data with repeated measurement. Cluster analysis seeks to division a given dataset into groups based on specified features so that the data points within a group are more similar to each other than the points in different groups. The gene ontology is a gene(gene products)using terms from three structured vocabularies: Biological process, cellular component and molecular function. For measuring the semantic similarity on GO terms using novel method, namely shortest path (SP) algorithm.

Keywords: Clustering, Gene Ontology, Shortest path, Semantic similarity, Novel method