It also

provides interfaces for data retrieval, analysis

It also

provides interfaces for data retrieval, analysis and visualization. SMD has its source code fully and freely available to others under an Open Source Licence, enabling other groups to create a local installation of SMD (www.ncbi.nih.gov/pubmed). The DEG holds information on essential genes from a number of organisms.16 and 17 The current release 6.3 contains information on 11,392 essential genes from various organisms both prokaryotes and eukaryotes. A typical entry includes a database specific accession number, the common gene name. GI reference, function, organism, reference and nucleotide sequence (www.essentialgene.org). ABT-888 manufacturer With the explosion of microarray data there is an emerging need to develop tools that learn more can statistically analyze the gene expression data. There are many tools available on net for the same. Cluster is a tool for data clustering of genes on the basis of gene expression data. It is available at Eisen Lab and can run on Windows. It uses many clustering algorithms which include

K-means, hierarchical, self-organizing map. The genes were clustered assuming the fact that genes that co-express along with the known virulent genes may also be responsible for the virulence.15 Basic Local Alignment Search Tool, or BLAST, was used for primary biological sequence information comparison. BLAST2 was used for the identification of paralogs for virulent genes. BLASTP was used for protein sequence comparison available on the home page of DEG and also was done for human genome and microbial genome BLAST (www.blastncbi.nlm.nih.gov.in). In the study well-reported virulent genes for S. pneumoniae were taken from VFDB. Next the gene expression data was downloaded with a time gap of 8–12 h. Data was normalized for further study. 4-Aminobutyrate aminotransferase To predict probable virulent genes normalized gene expression data was

analyzed by the help of cluster software using K-mean clustering algorithm and found 450 clusters. In K-means clustering, the numbers of clusters are designated (450), and then each gene is assigned to one of the K clusters by this algorithm before calculating distances. When a gene is found to be closer to the centroid of another cluster, it is reassigned. This is a very fast algorithm, but the number of clusters reported will be the K that was predetermined and it will not link them together as in the hierarchical clustering. Output of the clustering comes as a file containing different gene id(s) in 450 clusters. The genes that are co-expressed along with the virulent genes previously known are then isolated from the output file and their corresponding sequences of their product were downloaded from the NCBI. To predict more virulent genes search for paralogous genes was also done. This was done by using BLAST2 from NCBI. Essential genes are those indispensable for the survival or organism, and therefore their products are considered as a foundation of life.

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