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search optimization » swarm optimization (Expand Search), lead optimization (Expand Search), path optimization (Expand Search)
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Showing 1 - 20 results of 56 for search '(( binary data codes optimization algorithm ) OR ( library based search optimization algorithm ))', query time: 0.59s Refine Results
  1. 1
    S1 Data -

    S1 Data - by Haoqiang Liu (193675)

    Published 2021
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  2. 2
    The Pseudo-Code of the IRBMO Algorithm.

    The Pseudo-Code of the IRBMO Algorithm. by Chenyi Zhu (9383370)

    Published 2025
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  3. 3
    Train test validation libraries.

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

    Published 2021
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  4. 4
    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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  5. 5
    SSA4LSMOP

    SSA4LSMOP by Zongbin Qiao (19814199)

    Published 2024
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  6. 6
    Pseudo Code of RBMO.

    Pseudo Code of RBMO. by Chenyi Zhu (9383370)

    Published 2025
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  7. 7
    Microsoft excel file containing exhaustive list of Abbreviated-Injury Scale codes used to generate binary variables encoding the presence or absence of injury to various body regions/organ systems.

    Microsoft excel file containing exhaustive list of Abbreviated-Injury Scale codes used to generate binary variables encoding the presence or absence of injury to various body regio... by Michael D. Cobler-Lichter (22492930)

    Published 2025
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  8. 8
    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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  9. 9
    Training parameters for SpeCollate.

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

    Published 2021
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  10. 10
    Peptides.

    Peptides. by Muhammad Usman Tariq (11022141)

    Published 2021
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  11. 11
    Fig 9 -

    Fig 9 - by Muhammad Usman Tariq (11022141)

    Published 2021
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  12. 12
    UMAP.

    UMAP. by Muhammad Usman Tariq (11022141)

    Published 2021
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  13. 13
    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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  14. 14
    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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  15. 15
    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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  16. 16
    Fig 6 -

    Fig 6 - by Muhammad Usman Tariq (11022141)

    Published 2021
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  17. 17
    Online sextuplet mining for SNAP-loss.

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

    Published 2021
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  18. 18
    SpeCollate: Deep Similarity Network for proteomics.

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

    Published 2021
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  19. 19
    A generic proteomics flow.

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

    Published 2021
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  20. 20
    Space transition methods.

    Space transition methods. by Muhammad Usman Tariq (11022141)

    Published 2021
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