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Discovery proteomics software for the quantitative analysis of isobarically labeled DDA data, and the qualitative analysis of DDA, DIA, and PRM data.

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Product number: Sw-3001

Shotgun proteomics, also known as data-dependent acquisition (DDA), plays an important role in the generation of spectral libraries, qualitative proteome analysis, and the identification of post-translational modifications. In addition, recent innovations in isobaric labeling quantification, with the introduction of novel tags and wider multiplexing options, add accurate quantification of the proteome and widen the applications of shotgun proteomics for quantitative analysis.

SpectroMine™ expands the possibilities for researchers in shotgun proteomics:

  • DIA, DDA and PRM Searchable: Increased versatility with the opportunity to search multiple data-acquisition formats.
  • Scalability to 1’000s of Runs: Memory-efficient data handling enables concurrent processing of >1’000 of MS runs.
  • Accurate Statistics: FDR control on PSM, peptide, and protein level.
  • Differential Abundance Analysis: Detect previously undetectable information contrasting different biological or medical conditions.
  • GO Support: Link your protein identifications to gene ontology annotations.
  • All-In-One Workflow: With integrated quality control, spectra, and post-analysis visualization.
  • Isobaric Labeling Quantification: Compatible with Tandem Mass Tags (TMT), iTRAQ and EASI-tag reagents.


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Supported Instruments

  • Thermo Scientific™ Q Exactive™ Series
  • Thermo Scientific™ Orbitrap Fusion™ Series
  • AB SCIEX TripleTOF® Series (5600, 5600+, 6600)
  • Bruker Impact II
  • Bruker timsTOF and timsTOF Pro without Ion Mobility
  • Waters Xevo G2-XS


Supported Methods and Workflows

SpectroMine™ can search DDA, DIA, and PRM with MS1 information.

SpectroMine™ can search and quantify DDA runs from isobaric-labeled experiments using labels such as TMT, EASI-tag, and iTRAQ.

MS2 and SPS-MS3 methods are supported. All ion trap resolutions are supported. SpectroMine™ supports neutral loss-based fragmentation label methods (such as EASI-tag).


System Requirements

Operating System: Windows 7, x64
CPU: Intel® Core™, 2.7 GHz (quad-core) or similar
Hard drive: 200 GB free space
Memory:  16 GB
Software: .NET Framework 4.7 

Operating System: Windows 10 or higher, x64
CPU: Intel® Core™ i7 4770, 3.4 GHz (octa-core) or similar
Hard drive: 500 GB free space, solid state drive (SSD)
Memory:  64 GB or more
Software: .NET Framework 4.7 or higher


How to Order

Please submit a request form. Our team will review your inquiry and get back to you within 1 working day.


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Visit Science Hub to access all scientific and technical content (publications, videos, application notes, posters and more) related to Biognosys technology, products, and services.

How to Cite:

Lynn Verbeke, Oliver M. Bernhardt, Tejas Gandhi, Roland Bruderer, Lukas Reiter, Pulsar:
A Search Engine Integrated into Spectronaut using Dynamic PSM Stratification, Biognosys AG, ASMS 2017, San Diego, USA

Peer-Reviewed Papers

  1. Christina Ludwig, Ludovic Gillet, George Rosenberger, Sabine Amon, Ben C Collins, Ruedi Aebersold, Data‐independent acquisition‐based SWATH‐MS for quantitative proteomics: A Tutorial, Mol Syst Biol. (2018) 14: e8126
  2.  Frank Koopmans  Jenny T. C. Ho  August B. Smit  Ka Wan Li, Comparative Analyses of Data Independent Acquisition Mass Spectrometric Approaches: DIA, WiSIM‐DIA, and Untargeted DIA, Proteomics 2018, 18, 1700304
  3. Vadim Demichev, Christoph B. Messner, Kathryn S. Lilley, Markus Ralser, DIA-NN: Deep neural networks substantially improve the identification performance of Data-independent acquisition (DIA) in proteomics

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