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proteomics optimization » process optimization (Expand Search), potency optimization (Expand Search)
utilization algorithm » initialization algorithm (Expand Search), optimization algorithms (Expand Search), maximization algorithm (Expand Search)
source utilization » resource utilization (Expand Search), resource utilisation (Expand Search), service utilization (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
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Showing 1 - 20 results of 28 for search '(( binary data source utilization algorithm ) OR ( less based proteomics optimization algorithm ))', query time: 0.67s Refine Results
  1. 1
    A generic proteomics flow.

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

    Published 2021
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  2. 2
    SpeCollate: Deep Similarity Network for proteomics.

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

    Published 2021
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  3. 3
    Table1_Fine tuning a logical model of cancer cells to predict drug synergies: combining manual curation and automated parameterization.DOCX

    Table1_Fine tuning a logical model of cancer cells to predict drug synergies: combining manual curation and automated parameterization.DOCX by Åsmund Flobak (789984)

    Published 2023
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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
    Space transition methods.

    Space transition methods. by Muhammad Usman Tariq (11022141)

    Published 2021
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  15. 15
    Characteristics of training dataset used.

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

    Published 2021
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  16. 16
    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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  17. 17
    Datasets.

    Datasets. by Muhammad Usman Tariq (11022141)

    Published 2021
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  18. 18
    Fig 7 -

    Fig 7 - by Muhammad Usman Tariq (11022141)

    Published 2021
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  19. 19
    Train test validation libraries.

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

    Published 2021
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  20. 20
    Dataflow programming for the analysis of molecular dynamics with AViS, an analysis and visualization software application

    Dataflow programming for the analysis of molecular dynamics with AViS, an analysis and visualization software application by Kai Pua (8741547)

    Published 2020
    “…To overcome this problem, we designed a software application called AViS which focuses on the extensibility of analysis. By utilizing the dataflow programming (DFP) paradigm, algorithms can be defined by execution graphs, and arbitrary data can be transferred between nodes using visual connectors. …”
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