The LINCS program aims to generate an extensive reference set of cellular response signatures to a variety of small molecule and genetic perturbations. The goal is to create a sustainable and widely accessible knowledge resource to advance our understanding of the highly orchestrated interplay of molecular biological components in maintaining healthy development and how their perturbation causes disease. The data sets produced at LINCS span a variety of assay formats and technologies, including biochemical and single cell phenotypic responses, and genome-wide transcriptional profiling.
The success of this initiative critically relies on an effective informatics solution to integrate the various (current and future) data types generated in LINCS, as well as other large-scale screening efforts (such as the Molecular Libraries Probe Center Network, MLPCN) into coherent data sets and to make them accessible, interpretable, and actionable for scientists of different backgrounds and with different objectives. We propose to develop a novel knowledge-based, extensible information system of interconnected components that leverages semantic-web technologies and domain level ontologies. This system is called LIFE (LINCS Information FramEwork).
The long-term goal of the LIFE system is seamless “on-the fly” data integration and analysis via a semantic “Linked Data” approach that is scalable with respect to information volume and complexity. LIFE will incorporate biomedical domain-level ontologies, including our recently developed BioAssay Ontology (BAO), to semantically associate related data types and to provide a knowledge context of the underlying experiments and screening outcomes.
A key feature of LIFE will be the potential to derive novel implicit knowledge by various inference mechanisms; similar to how humans obtain insights by (mentally) connecting different pieces of information. The overarching goal of this proposed LIFE system is to help scientists to use data and results produced in the LINCS and other NIH screening programs in their own research and to support their translation towards the development of novel therapeutics.
For more information about the Library of Integrated Network-Based Cellular Signatures (LINCS), visit their website at http://commonfund.nih.gov/lincs/