Targeted drug discovery is data-intensive and involves extracting statistical trends from events of interest collected over a large population. But, relevant data in biomedical research is often hard to find. High throughput experiments churn up data quickly, but much of it is devoid of context due to missing labels, wrong annotations, and irretrievable storage.
And in the case of predicting rare events – such as cell lines that respond to a specific drug – only a few thousand relevant samples will be available. Generating more data is essential, but we often do not sufficiently leverage existing data. Ontologies are key to good interoperability, enabling data & metadata integration and allowing researchers to leverage more of what is known in their scientific domains to make data-driven decisions faster. In addition, the advanced relationships in ontologies help mine for unexpected co-occurrences and suggest novel uses of drugs or similarities between diseases. This webinar will demonstrate how ontologies are essential to understanding the incoming data deluge for an enterprise & how they help retrieve the most relevant data for R&D efforts.
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