Showing 161 - 180 results of 4,244 for search '(( algorithm density function ) OR ( algorithm ((protein function) OR (python function)) ))', query time: 0.84s Refine Results
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    Table2_Predicting Human Protein Subcellular Locations by Using a Combination of Network and Function Features.XLSX by Lei Chen (54296)

    Published 2021
    “…In this study, the proteinprotein interaction network, functional annotation of proteins and a group of direct proteins with known subcellular localization were used to construct models. …”
  3. 163

    Table3_Predicting Human Protein Subcellular Locations by Using a Combination of Network and Function Features.XLSX by Lei Chen (54296)

    Published 2021
    “…In this study, the proteinprotein interaction network, functional annotation of proteins and a group of direct proteins with known subcellular localization were used to construct models. …”
  4. 164

    Table4_Predicting Human Protein Subcellular Locations by Using a Combination of Network and Function Features.XLSX by Lei Chen (54296)

    Published 2021
    “…In this study, the proteinprotein interaction network, functional annotation of proteins and a group of direct proteins with known subcellular localization were used to construct models. …”
  5. 165

    Table1_Predicting Human Protein Subcellular Locations by Using a Combination of Network and Function Features.XLSX by Lei Chen (54296)

    Published 2021
    “…In this study, the proteinprotein interaction network, functional annotation of proteins and a group of direct proteins with known subcellular localization were used to construct models. …”
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    Density fit example. by Jared Adolf-Bryfogle (431729)

    Published 2024
    “…In this work, we developed a glycan-modeling algorithm, <i>GlycanTreeModeler</i>, that computationally builds glycans layer-by-layer, using adaptive kernel density estimates (KDE) of common glycan conformations derived from data in the Protein Data Bank (PDB) and from quantum mechanics (QM) calculations. …”
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    Predicting the Mutagenic Activity of Nitroaromatics Using Conceptual Density Functional Theory Descriptors and Explainable No-Code Machine Learning Approaches by Andrés Halabi Diaz (20798460)

    Published 2025
    “…This study integrates conceptual density functional theory (CDFT) descriptors with explainable no-code machine learning (ML) models to predict NA mutagenicity based on Ames test results. …”
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