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The DIP database catalogs experimentally determined interactions between proteins. It combines information from a variety of sources to create a single, consistent set of protein-protein interactions. The data stored within the DIP database were curated, both, manually by expert curators and also automatically using computational approaches that utilize the the knowledge about the protein-protein interaction networks extracted from the most reliable, core subset of the DIP data. Please, check the reference page to find articles describing the DIP database in greater detail. The Database of Ligand-Receptor Partners (DLRP) is a subset of DIP (Database of Interacting Proteins). The DLRP is a database of protein ligand and protein receptor pairs that are known to interact with each other. By interact we mean that the ligand and receptor are members of a ligand-receptor complex and, unless otherwise noted, transduce a signal. In some instances the ligand and/or receptor may form a heterocomplex with other ligands/receptors in order to be functional. We have entered the majority of interactions in DLRP as full DIP entries, with links to references and additional information
ASAP (a systematic annotation package for community analysis of genomes) is a relational database and web interface developed to store, update and distribute genome sequence data and gene expression data collected by or in collaboration with researchers at the University of Wisconsin - Madison. ASAP was designed to facilitate ongoing community annotation of genomes and to grow with genome projects as they move from the preliminary data stage through post-sequencing functional analysis. The ASAP database includes multiple genome sequences at various stages of analysis, and gene expression data from preliminary experiments.
The Cancer Cell Line Encyclopedia project is a collaboration between the Broad Institute, and the Novartis Institutes for Biomedical Research and its Genomics Institute of the Novartis Research Foundation to conduct a detailed genetic and pharmacologic characterization of a large panel of human cancer models, to develop integrated computational analyses that link distinct pharmacologic vulnerabilities to genomic patterns and to translate cell line integrative genomics into cancer patient stratification. The CCLE provides public access to genomic data, analysis and visualization for about 1000 cell lines.
The PhenoGen website shares experimental data with a worldwide community of investigators and provides a flexible, integrated, multi-resolution repository of neuroscience transcriptomic genetic data for collaborative research on genomic disorders. The main development focus is on providing Hybrid Rat Diversity Panel transcriptomic data (sequencing, genome coverage, reconstructed totalRNA/smallRNA transcriptomes, quanification of the transcriptome, eQTLs, and WGCNA) and integrating additional tools to provide platform for visualization and analysis of HRDP transcriptome data.
This site is now made possible by University of Canterbury, New Zealand, and serves as historical repository of collections of files once housed at datacenterhub (without the interactive tools that were available on that site). Former description: We offer a public platform to help researchers organize, share, and explore their research data. DataCenterHub provides a simple, standardized yet flexible platform to preserve and share data. In the future, this platform will offer data visualization tools and the ability to compare directly data from different sources.