A Novel Anticlustering Filtering Algorithm for the Prediction of Genes as a Drug Target

摘要: The high-throughput data generated by microarray experiments provides complete set of genes being expressed in a g iven cell or an organis m under part icular conditions. analysis these enormous has opened new dimension for the researchers. In this paper we describe novel algorith to focusing on identification that are differentially particular internal external conditions and which could be potential drug targets. algorithm uses time -series gene expression as input recognizes differentially. This imp lements standard statistics-based functional investigations, such log transformation, mean, log-sig moid function, coefficient variations, etc. It does not use clustering analysis. proposed been implemented Perl. time-series exp ression yeast Saccharomyces cerevisiae fro Stanford Microarray Database (SMD) consisting 6154 have taken validation o f m. developed method extracted 48 out total genes. These mostly responsible yeast's resistants at high temperature.