By comparing drugs and genetic targets, researchers can more easily identify pharmaceuticals that could be effective against different forms of cancer.
The newly updated software, called CellMiner, was built for use with the NCI-60, one of the most widely utilised collections of cancer cell samples employed in the testing of potential anti-cancer drugs. The tools provide rapid access to data from 22,379 genes catalogued in the NCI-60 and from 20,503 previously analysed chemical compounds.
"Previously you would have to hire a bioinformatics team to sort through all of the data, but these tools put the entire database at the fingertips of any researcher," explained Doctor Yves Pommier. "These tools allow researchers to analyse drug responses as well as make comparisons from drug to drug and gene to gene."
Genomic sequencing and analysis have become increasingly important in biomedicine, but they are yielding data sets so vast that researchers may find it difficult to access and compare them.
As new technologies emerge and more data are generated, tools to facilitate the comparative study of genes and potentially promising drugs will be of even greater importance. With the new tools researchers can compare patterns of drug activity and gene expression, not only to each other but also to other patterns of interest. CellMiner allows the input of large quantities of genomic and drug data, calculates correlations between genes and drug activity profiles, and identifies correlations that are statistically significant. Its data integration capacities are easier, faster, and more flexible than other available methods, and these tools can be adapted for use with other collections of data.
"We are looking forward to seeing how other people are going to use this tool to look at gene co-regulation, regulation of gene expression, and the relationship between gene expression and cancer," said Pommier.
MEDICA.de; Source: NIH/National Cancer Institute