Automated Lead Discovery and Development in HTS Datasets

The analysis of biological screening results has traditionally been a labor intensive process. Scientists familiar with the biological data under investigation would visually inspect the results, evaluate the quality and promise of active data points and identify leads. The introduction and widespread use of high throughput screening systems has increased the size of biological datasets immensely thus pushing the traditional analysis method to its limits. In this presentation we describe a new automated approach that emulates the decision making process of human experts. This approach combines knowledge-based techniques with human expertise to enable rapid identification, characterization and prioritization of lead candidates.