Laboratory information and management systems | Mass spectrometry-based untargeted proteomics
MS-based proteomics produces large amounts of mass spectra that require processing, identification and possibly quantification before interpretation can be undertaken. High-throughput studies require automation of these various steps, and management of the data in association with the results obtained.
A platform for management and analysis of proteomics LC-MS/MS data. MASPECTRAS assists researchers in understanding their data and publishing through sample comparisons, targeted queries, summaries, and exports in multiple formats such as PRIDE XML. MASPECTRAS also comprises mechanisms to facilitate its integration in a high-throughput infrastructure.
Supports interactive data exploration to efficiently interact with the data through graphical viewers and data filters. Prequips is an integrative software platform for comparative proteomics-based systems biology analysis that: (i) integrates all information generated from mass spectrometry (MS)- based proteomics as well as from basic proteomics data analysis tools, (ii) visualizes such information for various proteomic analyses via graphical interfaces and (iii) links peptide and protein abundances to external tools often used in systems biology studies.
Contains an entire data analysis and management pipeline for liquid chromatography tandem mass spectrometry (LC-MS/MS) proteomics, including experiment annotation, protein database searching and sequence management, and mining LC-MS/MS peptide and protein identifications. CPAS architecture and features, such as a general experiment annotation component, installation software, and data security management, make it useful for collaborative projects across geographical locations and for proteomics laboratories without substantial computational support.
The application features sample tracking, project sharing between multiple users, and automated data merging and analysis. ProSE has built-in support for several quantitative proteomics workflows, and integrates searching in several search engines, automated combination of the search results with predetermined false discovery rates, annotation of proteins and submission of results to public repositories. ProSE also provides a programming interface to enable local extensions, as well as database access using Web services. ProSE provides an analysis platform for proteomics research and is targeted for multiuser projects with needs to share data, sample tracking, and analysis result.
A freely available, open-source system based on a central database to automate data management and processing in mass spectrometry driven proteomics analyses. ms-lims is mainly designed to automate data flow in the high-throughput proteomics lab. Taking spectrum files from a variety of pluggable file formats, it transforms these to the Mascot Generic Format and stores them in the database, retaining LC information if present, and also allowing additional information to be stored for each individual LC run. Another part allows the retrieval of the stored spectra in mergefiles of arbitrary size. These can then be submitted to a search engine, eg. Mascot from Matrix Science. Subsequently, the results of these searches can be parsed and stored in a relational database structure for future reference.
An open source LIMS appropriately customized for 2-D gel electrophoresis-based proteomics workflow. The main features of its design are compactness, flexibility and connectivity to public databases. LIPAGE supports the handling of data imported from mass spectrometry software and 2-D gel image analysis software. The LIMS is equipped with the same input interface for 2-D gel information as a clickable map on public 2DPAGE databases. The LIMS allows researchers to follow their own experimental procedures by reviewing the illustrations of 2-D gel maps and well layouts on the digestion plates and MS sample plates.
Consists of a laboratory information management system (LIMS). DataManager enables the storage of detailed set of metadata associated with each experiment. Users can (i) capture and store metadata, (ii) automatically submit and monitor mass spectrometry (MS) sample, and log all raw data files from MS experiments, and (iii) search datasets for proteins and peptides of interest.
Merges protein summaries from multiple experimental quantitative proteomics data. PGCA connects two or more groups with overlapping accession numbers. The groups created by this tools from multiple experimental runs are called "connected" groups. These identified protein groups allow the analysis of quantitative data available for protein groups instead of unique protein identifiers.