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Showing 1 to 5 of 5 for “"Tanimoto similarity"”.

  1. Development of Machine Learning Models for Generation and Activity Prediction of the Protein Tyrosine Kinase Inhibitors

    … features of SRC Kinase Inhibitors. We then used similarity metrics such as Tanimoto Similarity to assess their closeness to that of known SRC Kinase Inhibitors. The molecules generated from this experiment demonstrated potential for belonging to the SRC Kinase Inhibitor family though chemical …

    chapman Repository record for Development of Machine Learning Models for Generation and Activity Prediction of the Protein Tyrosine Kinase Inhibitors (opens in a new tab)

  2. Automatic segmentation of magnetic resonance images of the brain

    … segmentations done by expert radiologists. The Tanimoto similarity coefficient was very good for the lateral ventricles (0.81) and good for the caudate nuclei (0.67).

    lsu-thes Repository record for Automatic segmentation of magnetic resonance images of the brain (opens in a new tab)

  3. Machine learning in predictive toxicology: investigating developmental and reproductive toxicity with transfer learning

    … Chapter 3 of this work investigates the use of Tanimoto similarity to determine the suitability of using transfer learning. It was found that when the predicted test accuracy (P) or the average similarity between datasets (S) is 70% or more, the machine learning model is likely to have high test …

    cambridge Repository record for Machine learning in predictive toxicology: investigating developmental and reproductive toxicity with transfer learning (opens in a new tab)

  4. Improving reproducibility and standards in quantitative N-Glycoproteomic data

    … — Relative Assessment of m/z Identifications by Similarity — was developed. This toolkit focuses on data quality assessment and identifying broad differences between glycosylation sites. RAMZIS uses a series of permutation tests with a weighted Tanimoto similarity assessment, it provides …

    bu Repository record for Improving reproducibility and standards in quantitative N-Glycoproteomic data (opens in a new tab)

  5. Advances in high-throughput screening: better compounds, novel targets, enhanced sensors

    High throughput screening (HTS) is the dominant force in modern drug discovery. Through the evaluation of large structure collections, novel drug leads can be rapidly assessed for modulation of medicinally-relevant biological targets. This occurs through the interplay of three intrinsically linked …

    uiuc Repository record for Advances in high-throughput screening: better compounds, novel targets, enhanced sensors (opens in a new tab)