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proteomics optimization » process optimization (Expand Search), potency optimization (Expand Search)
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Showing 1 - 20 results of 32 for search '(( library based proteomics optimization algorithm ) OR ( binary _ common optimization algorithm ))', query time: 0.60s Refine Results
  1. 1
    Train test validation libraries.

    Train test validation libraries. by Muhammad Usman Tariq (11022141)

    Published 2021
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  2. 2
    Binary contingency table.

    Binary contingency table. by Lu Xiao (314030)

    Published 2024
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  3. 3
    A generic proteomics flow.

    A generic proteomics flow. by Muhammad Usman Tariq (11022141)

    Published 2021
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  4. 4
    SpeCollate: Deep Similarity Network for proteomics.

    SpeCollate: Deep Similarity Network for proteomics. by Muhammad Usman Tariq (11022141)

    Published 2021
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  5. 5
    Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results

    Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results by Se-Hee Jo (20554623)

    Published 2025
    “…The algorithm was applied to aqueous, binary mixture systems composed of 37 common biochemical substances such as amino acids, organic acids, and sugars. …”
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  6. 6
    Closed search (±5ppm) comparison against Crux and MSFragger using real-world data from PRIDE repository PXD000612 (top), PXD009861 (middle), and PXD001468 (bottom).

    Closed search (±5ppm) comparison against Crux and MSFragger using real-world data from PRIDE repository PXD000612 (top), PXD009861 (middle), and PXD001468 (bottom). by Muhammad Usman Tariq (11022141)

    Published 2021
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  7. 7
    Training parameters for SpeCollate.

    Training parameters for SpeCollate. by Muhammad Usman Tariq (11022141)

    Published 2021
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  8. 8
    Peptides.

    Peptides. by Muhammad Usman Tariq (11022141)

    Published 2021
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  9. 9
    Fig 9 -

    Fig 9 - by Muhammad Usman Tariq (11022141)

    Published 2021
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  10. 10
    UMAP.

    UMAP. by Muhammad Usman Tariq (11022141)

    Published 2021
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  11. 11
    Process of generating MS/MS spectra from a protein mixture using mass-spectrometry analysis.

    Process of generating MS/MS spectra from a protein mixture using mass-spectrometry analysis. by Muhammad Usman Tariq (11022141)

    Published 2021
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  12. 12
    Modifications and the character values used in the training data.

    Modifications and the character values used in the training data. by Muhammad Usman Tariq (11022141)

    Published 2021
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  13. 13
    2D UMAP visualization of embedded spectra and peptide vectors generated by SpeCollate.

    2D UMAP visualization of embedded spectra and peptide vectors generated by SpeCollate. by Muhammad Usman Tariq (11022141)

    Published 2021
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  14. 14
    Fig 6 -

    Fig 6 - by Muhammad Usman Tariq (11022141)

    Published 2021
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  15. 15
    Online sextuplet mining for SNAP-loss.

    Online sextuplet mining for SNAP-loss. by Muhammad Usman Tariq (11022141)

    Published 2021
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  16. 16
    Space transition methods.

    Space transition methods. by Muhammad Usman Tariq (11022141)

    Published 2021
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  17. 17
    Characteristics of training dataset used.

    Characteristics of training dataset used. by Muhammad Usman Tariq (11022141)

    Published 2021
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  18. 18
    Venn diagrams showing the overlap of peptides among SpeCollate, Crux, and MSFragger.

    Venn diagrams showing the overlap of peptides among SpeCollate, Crux, and MSFragger. by Muhammad Usman Tariq (11022141)

    Published 2021
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  19. 19
    Datasets.

    Datasets. by Muhammad Usman Tariq (11022141)

    Published 2021
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  20. 20
    Fig 7 -

    Fig 7 - by Muhammad Usman Tariq (11022141)

    Published 2021
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