The LINCS program has transitioned from Common Fund support. For more information, please visit the LINCS website.

Please note that since the LINCS program is no longer supported by the Common Fund, the program website is being maintained as an archive and will not be updated on a regular basis.

Advances in technology have allowed scientists to study the basic components of biological systems—genes, proteins, and other molecules—together as a group instead of one at a time. Scientists have found more and more that biological processes driven by these components are extremely interconnected, and alteration in one component of the system can have dramatic and difficult-to-predict effects on many of the other components. Understanding interconnectedness at a system-wide level can help develop new and better therapies to return disrupted biological processes back to their natural state.

To achieve this goal, the LINCS program generated data to identify patterns of cellular responses to various stress signals. These cellular responses included changes in gene expression and other cellular characteristics. The underlying idea for the LINCS program was that disrupting any step of a biological process will cause related changes in the characteristics, behavior, and/or function of the cell. Comparing the patterns of the cells’ responses to different stress signals can provide clues about the underlying mechanisms involved in disease processes. LINCS developed and used computational tools to integrate data about cellular responses into a comprehensive view of normal and disease states. This knowledge has helped researchers identify chemicals that can kill diseased cells or return them to a healthier state. As such chemicals are identified, they are forming the basis of new therapeutics.

LINCS data and tools are freely available as a resource for the biomedical research community to explore how cells respond to various genetic, chemical, and environmental stressors. The data can also be searched for a particular cellular response to identify new drug candidates related to that response. The LINCS data resource has allowed for far greater discovery and public health impact beyond the work of the individual investigators that were funded through the LINCS program.