Database search engine

Abstract: We present a statistical model to estimate the accuracy of peptide assignments to tandem mass (MS/MS) spectra made by database search applications such as SEQUEST. Employing the expectation maximization algorithm, the analysis learns to distinguish correct from incorrect database search results, computing probabilities that peptide assignments to spectra are correct based upon database search scores and the number of tryptic termini of peptides. Using SEQUEST search results for spectra generated from a sample of known protein components, we demonstrate that the computed probabilities are accurate and have high power to discriminate between correctly and incorrectly assigned peptides. This analysis makes it possible to filter large volumes of MS/MS database search results with predictable false identification error rates and can serve as a common standard by which the results of different research groups are compared.

Abstract: Proteomics research routinely involves identifying peptides and proteins via MS/MS sequence database search. Thus the database search engine is an integral tool in many proteomics research groups. Here, we introduce the Comet search engine to the existing landscape of commercial and open-source database search tools. Comet is open source, freely available, and based on one of the original sequence database search tools that has been widely used for many years.

Abstract: According to one aspect of the present invention, a method includes displaying a search tool bar including a search icon. The method also includes displaying a search center pane after a user selects the search icon, wherein the search center pane includes a search frame. The method further includes selecting a search category from a dropdown list of search categories in the search frame. In addition, the method includes entering a search keyword. Furthermore, the method includes searching a database for data records matching the search category and the search keyword.