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search optimization » swarm optimization (Expand Search), lead optimization (Expand Search), path optimization (Expand Search)
robust detection » object detection (Expand Search), point detection (Expand Search), first detection (Expand Search)
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binary basic » binary mask (Expand Search)
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Showing 1 - 20 results of 47 for search '(( library based search optimization algorithm ) OR ( binary basic robust detection algorithm ))', query time: 0.57s 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
    ReaLigands: A Ligand Library Cultivated from Experiment and Intended for Molecular Computational Catalyst Design

    ReaLigands: A Ligand Library Cultivated from Experiment and Intended for Molecular Computational Catalyst Design by Shu-Sen Chen (1777108)

    Published 2023
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  3. 3
    SSA4LSMOP

    SSA4LSMOP by Zongbin Qiao (19814199)

    Published 2024
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  4. 4
    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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  5. 5
    Training parameters for SpeCollate.

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

    Published 2021
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  6. 6
    Peptides.

    Peptides. by Muhammad Usman Tariq (11022141)

    Published 2021
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  7. 7
    Fig 9 -

    Fig 9 - by Muhammad Usman Tariq (11022141)

    Published 2021
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  8. 8
    UMAP.

    UMAP. by Muhammad Usman Tariq (11022141)

    Published 2021
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  9. 9
    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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  10. 10
    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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  11. 11
    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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  12. 12
    Fig 6 -

    Fig 6 - by Muhammad Usman Tariq (11022141)

    Published 2021
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  13. 13
    Online sextuplet mining for SNAP-loss.

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

    Published 2021
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  14. 14
    SpeCollate: Deep Similarity Network for proteomics.

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

    Published 2021
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  15. 15
    A generic proteomics flow.

    A generic proteomics flow. 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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