MOTIVATION: Native top-down proteomics (nTDP) integrates native mass spectrometry (nMS) with top-down proteomics (TDP) to provide comprehensive analysis of protein complexes together with proteoform identification and characterization. Despite significant advances in nMS and TDP software developments, a unified and user-friendly software package for analysis of nTDP data remains lacking. RESULTS: We have developed MASH Native to provide a unified solution for nTDP to process complex datasets with database searching capabilities in a user-friendly interface. MASH Native supports various data formats and incorporates multiple options for deconvolution, database searching, and spectral summing to provide a "one-stop shop" for characterizing both native protein complexes and proteoforms. AVAILABILITY AND IMPLEMENTATION: The MASH Native app, video tutorials, written tutorials, and additional documentation are freely available for download at https://labs.wisc.edu/gelab/MASH_Explorer/MASHSoftware.php. All data files shown in user tutorials are included with the MASH Native software in the download .zip file.

DEVise is a data exploration system that allows users to easily develop, browse, and share visual presentation of large tabular datasets (possibly containing or referencing multimedia objects) from several sources. The DEVise framework is being implemented in a tool that has been already successfully applied to a variety of real applications by a number of user groups.

DEVise is a data exploration system that allows users to easily develop, browse, and share visual presentations of large tabular datasets (possibly containing or referencing multimedia objects) from several sources. The DEVise framework, implemented in a tool that has been already successfully applied to a variety of real applications by a number of user groups, makes several contributions. In particular, it combines support for extended relational queries with powerful data visualization features. Datasets much larger than available main memory can be handled—DEVise is currently being used to visualize datasets well in excess of 100MB—and data can be interactively examined at several levels of detail: all the way from meta-data summarizing the entire dataset, to large subsets of the actual data, to individual data records. Combining querying (in general, data processing) with visualizations gives us a very versatile tool, and presents several novel challenges.