Announcements

LINCS Data Science Research Webinars

May 24, 2016: Detection and Removal of Spatial Bias in Multi-Well Assays (Alexander Lachmann PhD, Columbia University)
Webinar Details

June 28, 2016Construction, Characterization and Validation of Multiscale Gene Networks in Cancer (Bin Zhang PhD, Icahn School of Medicine at Mount Sinai)
Webinar Details

NIH LINCS Program on Social Media

Follow the NIH LINCS Program on YouTube and on Twitter for information on the consortium’s latest news, data releases, and tools!

Phosphosignatures from the P100 Sentinel Assay

coverA study from the LINCS Proteomic Characterization Center for Signaling and Epigenetics was highlighted on the cover of the May 2016; 15 (5) issue of Molecular and Cellular Proteomics. For more details, see the article: Reduced-representation phosphosignatures measured by quantitative targeted MS capture cellular states and enable large-scale comparison of drug-induced phenotypes. PMID: 26912667

The LINCS Consortium

LINCS aims to create a network-based understanding of biology by cataloging changes in gene expression and other cellular processes that occur when cells are exposed to a variety of perturbing agents, and by using computational tools to integrate this diverse information into a comprehensive view of normal and disease states that can be applied for the development of new biomarkers and therapeutics. By generating and making public data that indicates how cells respond to various genetic and environmental stressors, the LINCS project will help us gain a more detailed understanding of cell pathways and aid efforts to develop therapies that might restore perturbed pathways and networks to their normal states.

The LINCS website is a source of information for the research community and general public about the LINCS project. The website contains details about the assays, cell types, and perturbagens currently part of the library, as well as links to participating sites, the data releases from the sites, and software that can be used for analyzing the data.