Scientific workflows as productivity tools for drug discovery.

Large pharmaceutical companies annually invest tens to hundreds of millions of US dollars in research informatics to support their early drug discovery processes. Traditionally, most of these investments are designed to increase the efficiency of drug discovery. The introduction of do-it-yourself scientific workflow platforms has enabled research informatics organizations to shift their efforts toward scientific innovation, ultimately resulting in a possible increase in return on their investments. Unlike the handling of most scientific data and application integration approaches, researchers apply scientific workflows to in silico experimentation and exploration, leading to scientific discoveries that lie beyond automation and integration. This review highlights some key requirements for scientific workflow environments in the pharmaceutical industry that are necessary for increasing research productivity. Examples of the application of scientific workflows in research and a summary of recent platform advances are also provided.

Computational dissection of tissue contamination for identification of colon cancer-specific expression profiles.

Microarray profiles of bulk tumor tissues reflect gene expression corresponding to malignant cells as well as to many different types of contaminating normal cells. In this report, we assess the feasibility of querying baseline multitissue transcriptome databases to dissect disease-specific genes. Using colon cancer as a model tumor, we show that the application of Boolean operators (AND, OR, BUTNOT) for database searches leads to genes with expression patterns of interest. The BUTNOT operator for example allows the assignment of "expression signatures" to normal tissue specimens. These expression signatures were then used to computationally identify contaminating cells within conventionally dissected tissue specimens. The combination of several logic operators together with an expression database based on multiple human tissue specimens can resolve the problem of tissue contamination, revealing novel cancer-specific gene expression. Several markers, previously not known to be colon cancer associated, are provided.