15 and 16 Another method that is drug target identification using side-effect similarity6 uses targets for drugs which have so far been predicted on the basis of molecular or cellular features, for example by exploiting similarity in chemical structure or in activity across cell lines. The study of gene expression has been greatly facilitated by DNA microarray technology.17 The anticipated floods of biological information produced by these experiments will open new doors into genetic analysis.18 Expression patters have already been used in a variety of tasks. Most bioresearch involves through the development of
technology used for carrying them out. It is not possible to research on a large number of genes using traditional methods. Microarray is one such technology which enables researchers to investigate an issue which were once thought to be non-traceable. One can analyze the expression of many genes in a single reaction www.selleckchem.com/products/ABT-888.html quickly and in an efficient www.selleckchem.com/products/Fludarabine(Fludara).html manner. Microarray technology has empowered the scientific community to understand the fundamental aspects the underlying the growth and development
of life as well as to explore the genetic causes of anomalies occurring in the functioning of human body. Researchers hope to find molecules that can be targeted for treatment with drugs amount the various protein encoded by disease- associated genes. The use of miniaturized microarrays for gene expression profiling was first reported in 1995, and a complete eukaryotic genome (Saccharomyces cerevisiae) on a microarray was published in 1996. 6 Clustering is the assignment of a set of observations into
subsets called clusters so that observations in the same cluster are similar in some sense. It is also a common technique used for statistical data analysis in many fields, including machine learning, data mining, pattern recognition, image analysis, information retrieval, and bioinformatics. Despite the availability of several drugs and vaccines, bacterial pathogenic diseases remain a major health problem and concern worldwide. This is due to the fact that bacteria become resistant to a particular antibiotic over the course of usage. The objectives of the present study are prediction of probable virulent gene, identification of paralogous genes and co-expressed genes, prediction of essentiality Methisazone of corresponding proteins and prediction of Putative Drug targets. VFDB is an integrated and comprehensive database of virulence factors of 24 bacterial pathogens.11 and 18 VFDB is comprehensive and user-friendly and one can search VFDB by browsing each genus or by typing keywords (www.mgc.ac.cn/vfs). Furthermore, a BLAST search tool against all known VF-related genes is also available. VFDB also provides a unified gateway to store, search, retrieve and update information about VFs from various bacterial pathogens. The SMD contains the largest amount of gene expression data from about 67 organisms.