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12 ta ish

Ish: Additive SMILES-based optimal descriptors in QSAR modelling bee toxicity: Using rare SMILES attributes to define the applicability domain

  1. SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules

    David Weininger

    Maqola198819 iqtibos
    ABI

  2. Prediction of Aquatic Toxicity:  Use of Optimization of Correlation Weights of Local Graph Invariants

    Andrey A. Toropov, T.W. Schultz

    Maqola200310 iqtibos
    ABI

  3. SMILES. 3. DEPICT. Graphical depiction of chemical structures

    David Weininger

    Maqola19908 iqtibos
    ABI

  4. SMILES. 2. Algorithm for generation of unique SMILES notation

    David Weininger, Arthur Weininger, J. L. Weininger

    Maqola19897 iqtibos
    ABI

  5. QSPR Modeling of Lipid-Water Partition Coefficient by Optimization of Correlation Weights of Local Graph Invariants

    Andrey A. Toropov, Kunal Roy

    MaqolaComputational Drug Discovery MethodsJournal of Chemical Information and Computer Sciences20037 iqtibos
    ABI

  6. Enhancement of the chemical semantic web through the use of InChI identifiers

    Simon J. Coles, Nick Day, Peter Murray‐Rust +2

    Maqola20052 iqtibos
    ABI

  7. SMILES as an alternative to the graph in QSAR modelling of bee toxicity

    Andrey A. Toropov, Emilio Benfenati

    Maqola20072 iqtibos
    ABI

  8. Sarlavhasiz

    Boshqa1 iqtibos
    ABI

  9. Sarlavhasiz

    Boshqa1 iqtibos
    ABI

  10. Sarlavhasiz

    Boshqa1 iqtibos
    ABI

  11. Sarlavhasiz

    Boshqa1 iqtibos
    ABI

  12. Sarlavhasiz

    Boshqa1 iqtibos
    ABI