Convolutional embedding of attributed molecular graphs for physical property prediction

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Items 101–200 of 469

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33. A machine learning workflow for molecular analysis: application to melting points
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34. Mol2Context-vec: learning molecular representation from context awareness for drug discovery
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39. Current development of integrated web servers for preclinical safety and pharmacokinetics assessments in drug development
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40. Combining Group-Contribution Concept and Graph Neural Networks Toward Interpretable Molecular Property Models
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41. Evaluation of deep and shallow learning methods in chemogenomics for the prediction of drugs specificity
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42. Accurate Prediction of Aqueous Free Solvation Energies Using 3D Atomic Feature-Based Graph Neural Network with Transfer Learning
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43. Prototype-Based Compound Discovery Using Deep Generative Models
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44. Making machine learning a useful tool in the accelerated discovery of transition metal complexes
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45. Constrained Bayesian Optimization for Automatic Chemical Design
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46. DeLA-Drug: A Deep Learning Algorithm for Automated Design of Druglike Analogues
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47. Topology-Based Machine Learning Strategy for Cluster Structure Prediction
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48. Predicting Adhesive Free Energies of Polymer–Surface Interactions with Machine Learning
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52. SolvBERT for solvation free energy and solubility prediction: a demonstration of an NLP model for predicting the properties of molecular complexes
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53. A spatial-temporal gated attention module for molecular property prediction based on molecular geometry
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54. Solubility Prediction from Molecular Properties and Analytical Data Using an In-phase Deep Neural Network (Ip-DNN)
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55. A comprehensive comparison of molecular feature representations for use in predictive modeling
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56. An overview of neural networks for drug discovery and the inputs used
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57. Predicting glass transition temperature and melting point of organic compounds via machine learning and molecular embeddings
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58. Automatic Prediction of Peak Optical Absorption Wavelengths in Molecules Using Convolutional Neural Networks
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59. CycPeptMP: enhancing membrane permeability prediction of cyclic peptides with multi-level molecular features and data augmentation
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60. Layer-wise relevance propagation of InteractionNet explains protein–ligand interactions at the atom level
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61. The challenges of generalizability in artificial intelligence for ADME/Tox endpoint and activity prediction
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62. Artificial Intelligence and Quantum Computing as the Next Pharma Disruptors
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65. Biomedical Data and Deep Learning Computational Models for Predicting Compound-Protein Relations
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66. Improved Lipophilicity and Aqueous Solubility Prediction with Composite Graph Neural Networks
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67. Dowker complex based machine learning (DCML) models for protein-ligand binding affinity prediction
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68. Determining influential descriptors for polymer chain conformation based on empirical force-fields and molecular dynamics simulations
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69. Data Science Approach to Estimate Enthalpy of Formation of Cyclic Hydrocarbons
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72. Virtual Screening Meets Deep Learning
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74. Interpretable Chirality-Aware Graph Neural Network for Quantitative Structure Activity Relationship Modeling in Drug Discovery
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80. Structure-Based Protein Function Prediction using Graph Convolutional Networks
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85. Describe Molecules by a Heterogeneous Graph Neural Network with Transformer-like Attention for Supervised Property Predictions
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