BioAssay Ontology (BAO) and the LINCS Information FramEwork (LIFE) to Integrate and Analyze Diverse High Throughput and Cellular Profiling Assay Data



July 15, 2013

The lack of established and accepted standards to describe and annotate biological assays and screening results in the domain of high throughput and high content screening (HTS, HCS) is a severe limitation to utilize these valuable datasets to their maximum potential. We developed BioAssay Ontology (BAO: to enable standardized description, integration and meta-­‐ analysis of various high throughput and profiling assay and screening results. BAO leverages Description Logic and Web Ontology Language to capture and formalize knowledge about assays and enable computational systems to utilize this knowledge. We illustrate our approach using data generated in the Library of Integrated Cellular Network-­‐based Signatures (LINCS) Program, a recent large-­‐scale systems biology data production and analysis effort funded by the NIH. Leveraging the ontology, we developed a semantic model to describe and integrate LINCS data. We implemented a semantic web software system, the LINCS Information FramEwork (LIFE: to exchange, query, and explore these datasets. Our approach facilitates the linking and classification of diverse entities, such small molecules, cellular model systems, diseases, gene and protein kinase targets, based on the underlying cellular profiling results.

Drug DiscoveryInformatics

ELA - Drug Discovery Automation: High-content Screening & Cell Based Assays 2013


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