Molecular Interaction Search Tool (MIST): an integrated resource for mining gene and protein interaction data
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CitationHu, Yanhui, Arunachalam Vinayagam, Ankita Nand, Aram Comjean, Verena Chung, Tong Hao, Stephanie E Mohr, and Norbert Perrimon. 2018. “Molecular Interaction Search Tool (MIST): an integrated resource for mining gene and protein interaction data.” Nucleic Acids Research 46 (Database issue): D567-D574. doi:10.1093/nar/gkx1116. http://dx.doi.org/10.1093/nar/gkx1116.
AbstractAbstract Model organism and human databases are rich with information about genetic and physical interactions. These data can be used to interpret and guide the analysis of results from new studies and develop new hypotheses. Here, we report the development of the Molecular Interaction Search Tool (MIST; http://fgrtools.hms.harvard.edu/MIST/). The MIST database integrates biological interaction data from yeast, nematode, fly, zebrafish, frog, rat and mouse model systems, as well as human. For individual or short gene lists, the MIST user interface can be used to identify interacting partners based on protein–protein and genetic interaction (GI) data from the species of interest as well as inferred interactions, known as interologs, and to view a corresponding network. The data, interologs and search tools at MIST are also useful for analyzing ‘omics datasets. In addition to describing the integrated database, we also demonstrate how MIST can be used to identify an appropriate cut-off value that balances false positive and negative discovery, and present use-cases for additional types of analysis. Altogether, the MIST database and search tools support visualization and navigation of existing protein and GI data, as well as comparison of new and existing data.
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