A web-based database and a knowledge extraction engine. Lynx supports annotation and analysis of high-throughput experimental data and generation of weighted hypotheses regarding genes and molecular mechanisms contributing to human phenotypes or conditions of interest. Since the last release, the Lynx knowledge base (LynxKB) has been periodically updated with the latest versions of the existing databases and supplemented with additional information from public databases. These additions have enriched the data annotations provided by Lynx and improved the performance of Lynx analytical tools. Moreover, the Lynx analytical workbench has been supplemented with new tools for reconstruction of co-expression networks and feature-and-network-based prioritization of genetic factors and molecular mechanisms. These developments facilitate the extraction of meaningful knowledge from experimental data and LynxKB. The Service Oriented Architecture provides public access to LynxKB and its analytical tools via user-friendly web services and interfaces.
Department of Human Genetics, University of Chicago, Chicago, IL, USA; Computation Institute, University of Chicago, Chicago, IL, USA; Department of Computer Science, Illinois Institute of Technology, Chicago, IL, USA; Toyota Technological Institute at Chicago, Chicago, IL, USA; Department of Medicine, University of Chicago, Chicago, IL, USA
Lynx funding source(s)
Mr and Mrs Lawrence Hilibrand, the Boler Family Foundation and National Institutes of Health/National Institute of Neurological Disorders and Stroke grant [NS050375, in part]; The Genetic Basis of Mid-Hindbrain Malformations; National Institute of Mental Health [1U24MH081810, in part]