LINCS Data Science Research Webinars
June 28, 2016: Construction, Characterization and Validation of Multiscale Gene Networks in Cancer (Bin Zhang PhD, Icahn School of Medicine at Mount Sinai)
Editorial: Reproducibility will only come with data liberation
In a recent editorial in Science Translational Medicine, Mohammed AlQuraishi and Peter Sorger from the HMS LINCS Center make the case for improving accessibility and usability of published experimental data of all data types. Read More
NIH LINCS Program on Social Media
Phosphosignatures from the P100 Sentinel Assay
A 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. Read More
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.