Browse publically available datasets or search by dataset metadata (e.g., species, PI, etc.). Datasets are available for download as well as for online browsing of submitted identifications (for complete datasets). Dataset owners can also add missing/requested files, update metadata and add publications to their datasets. Registered users can comment on datasets so others in the community can see updates or find pointers to new analyses of the data.

Submit your data to share with the community as a MassIVE dataset; reviewer access credentials and ProteomeXchange identifiers can be requested to meet publication guidelines of proteomics datasets (documentation here). Additional workflows are also available to convert vendor raw files (mass spectrometry data) to the open mzML format and to convert from common tab-separated formats (identifications data) into the open mzTab format.

Search all submitted identifications in complete datasets and dataset reanalyses. Over 300 million peptide-spectrum matches submitted with at most 1% false discovery rate are accessible through this simple interface to search for peptides, proteins and post-translational modifications.

Reanalyze public datasets using online MassIVE workflows for analysis of mass spectrometry data: MSGF+ database search, MSPLIT spectral library search, MODa open modification search, Maestro spectral networks search and MSPLIT-DIA for search of data-independent acquisition (DIA) spectra.

Compare identification results between datasets or against any reanalyses of public data. Venn diagrams are used to compare results at the level of protein, peptide and spectrum identifications; agreements, disagreements and unique identifications can be interactively inspected for assessment of quality of identifications.

Share your dataset reanalysis results with the community: reveal new identifications with novel algorithms / analysis pipelines or challenge previously submitted identifications with alternative interpretations for the same data.

Explore the translated evidence and sequence coverage of nearly every human protein, as defined by systematic reanalysis of 31 terabytes of public data from >20,000 LC/MS runs and including over 1 million synthetic peptide spectra. Interactive exploration of protein evidence includes coverage maps, functional sites, and full provenance and dataset mapping of every identified peptide.

Browse the community big data derived MassIVE Knowledge Base (MassIVE-KB) peptide spectral libraries. Distilled from 31TB of human proteomics HCD data. Users can peak at the inside of these libraries, browse the source data, and track full provenance of analysis tasks that created these libraries. Please refer to the documentation.

MassIVE.quant is an extension of the Mass Spectrometry Interactive Virtual Environment (MassIVE) to provide the opportunity for large-scale deposition of data from quantitative mass spectrometry-based proteomic experiments. MassIVE.quant is compatible with all mass spectrometry data acquisition types and all computational analysis tools. For each dataset, MassIVE.quant systematically stores the raw experimental data, the annotations of the experimental design, the scripts (or descriptions) of every step of the quantitative analysis workflow, and the intermediate input and output files. A branch structure enables MassIVE.quant to store and view alternative reanalyses of the same dataset with various combinations of methods and tools in a way which allows the user to inspect, reproduce or modify any component of the workflow, beginning with well-defined intermediate files. MassIVE.quant supports infrastructure to fully automate a analysis workflow, or to store, and to browse the intermediate results.

CoronaMassKB is an open-data community resource for sharing of mass spectrometry data and (re)analysis results for all experiments pertinent to the global SARS-CoV-2 pandemic. CoronaMassKB is designed for the rapid exchange of data and results among the global community of scientists working towards understanding the biology of SARS-CoV-2/COVID19 and thus accelerating the emergence of effective responses to this global pandemic.