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Yuhong Ning

Publications and source records attributed to Yuhong Ning.

3 recordsLinked to original sources

The alliance for cellular signaling plasmid collection: a flexible resource for protein localization studies and signaling pathway analysis.

Cellular responses to inputs that vary both temporally and spatially are determined by complex relationships between the components of cell signaling networks. Analysis of these relationships requires access to a wide range of experimental reagents and techniques, including the ability to express the protein components of the model cells in a variety of contexts. As part of the Alliance for Cellular Signaling, we developed a robust method for cloning large numbers of signaling ORFs into Gateway entry vectors, and we created a wide range of compatible expression platforms for proteomics applications. To date, we have generated over 3000 plasmids that are available to the scientific community via the American Type Culture Collection. We have established a website at www.signaling-gateway.org/data/plasmid/ that allows users to browse, search, and blast Alliance for Cellular Signaling plasmids. The collection primarily contains murine signaling ORFs with an emphasis on kinases and G protein signaling genes. Here we describe the cloning, databasing, and application of this proteomics resource for large scale subcellular localization screens in mammalian cell lines.

Animals↗

Overview of the Alliance for Cellular Signaling.

The Alliance for Cellular Signaling is a large-scale collaboration designed to answer global questions about signalling networks. Pathways will be studied intensively in two cells--B lymphocytes (the cells of the immune system) and cardiac myocytes--to facilitate quantitative modelling. One goal is to catalyse complementary research in individual laboratories; to facilitate this, all alliance data are freely available for use by the entire research community.

B-Lymphocytes↗

The Molecule Pages database.

The Alliance for Cellular Signaling (AfCS)-Nature Molecule Pages will be a comprehensive database of key facts about more than 3,000 proteins involved in cell signalling. Each entry will be created by invited experts and be peer-reviewed. Alongside the large-scale experiments being conducted by the AfCS scientists, the wealth of information contained in this database offers the potential of accelerating the pace of discovery in signal transduction research.

Automation↗