AIMC Journal:
Journal of chemical information and modeling

Showing 191 to 200 of 934 articles

Graph Curvature Flow-Based Masked Attention.

Journal of chemical information and modeling Oct 23, 2024
Graph neural networks (GNNs) have revolutionized drug discovery in chemistry and biology, enhancing efficiency and reducing resource demands. However, classical GNNs often struggle to capture long-range dependencies due to challenges like oversmoothi...
Neural Networks, Computer Drug Discovery Computer Graphics
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Uncertainty Qualification for Deep Learning-Based Elementary Reaction Property Prediction.

Journal of chemical information and modeling Oct 23, 2024
The prediction of the thermodynamic and kinetic properties of elementary reactions has shown rapid improvement due to the implementation of deep learning (DL) methods. While various studies have reported the success in predicting reaction properties,...
Deep Learning Kinetics Monte Carlo Method Thermodynamics Uncertainty
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Machine Learning-Driven Data Valuation for Optimizing High-Throughput Screening Pipelines.

Journal of chemical information and modeling Oct 23, 2024
In the rapidly evolving field of drug discovery, high-throughput screening (HTS) is essential for identifying bioactive compounds. This study introduces a novel application of data valuation, a concept for evaluating the importance of data points bas...
Machine Learning Drug Discovery Drug Evaluation, Preclinical High-Throughput Screening Assays
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Gotcha GPT: Ensuring the Integrity in Academic Writing.

Journal of chemical information and modeling Oct 22, 2024
This application note explores how to address a challenging problem faced by many academics and publishing professionals in recent years: ensuring the integrity of academic writing in universities and publishing houses due to advances in Artificial I...
Humans Artificial Intelligence Software Writing
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Multimodal Representation Learning via Graph Isomorphism Network for Toxicity Multitask Learning.

Journal of chemical information and modeling Oct 21, 2024
Toxicity is paramount for comprehending compound properties, particularly in the early stages of drug design. Due to the diversity and complexity of toxic effects, it became a challenge to compute compound toxicity tasks. To address this issue, we pr...
Humans Neural Networks, Computer Machine Learning Deep Learning Drug-Related Side Effects and Adverse Reactions
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Employing Machine Learning Models to Predict Potential α-Glucosidase Inhibitory Plant Secondary Metabolites Targeting Type-2 Diabetes and Their Validation.

Journal of chemical information and modeling Oct 1, 2024
The need for new antidiabetic drugs is evident, considering the ongoing global burden of type-2 diabetes mellitus despite notable progress in drug discovery from laboratory research to clinical application. This study aimed to build machine learning ...
Humans Machine Learning Diabetes Mellitus, Type 2 Hypoglycemic Agents Plants alpha-Glucosidases Glycoside Hydrolase Inhibitors Secondary Metabolism
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Gating-Enhanced Hierarchical Structure Learning in Hyperbolic Space and Multi-scale Neighbor Topology Learning in Euclidean Space for Prediction of Microbe-Drug Associations.

Journal of chemical information and modeling Sep 26, 2024
Identifying drug-related microbes may help us explore how the microbes affect the functions of drugs by promoting or inhibiting their effects. Most previous methods for the prediction of microbe-drug associations focused on integrating the attributes...
Neural Networks, Computer Machine Learning Algorithms Bacteria Pharmaceutical Preparations
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Deciphering Molecular Embeddings with Centered Kernel Alignment.

Journal of chemical information and modeling Sep 25, 2024
Analyzing machine learning models, especially nonlinear ones, poses significant challenges. In this context, centered kernel alignment (CKA) has emerged as a promising model analysis tool that assesses the similarity between two embeddings. CKA's eff...
Neural Networks, Computer Machine Learning Algorithms Models, Molecular Cheminformatics
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The Development and Application of KinomePro-DL: A Deep Learning Based Online Small Molecule Kinome Selectivity Profiling Prediction Platform.

Journal of chemical information and modeling Sep 25, 2024
Characterizing the kinome selectivity profiles of kinase inhibitors is essential in the early stages of novel small-molecule drug discovery. This characterization is critical for interpreting potential adverse events caused by off-target polypharmaco...
Humans Drug Discovery Deep Learning Protein Kinases Protein Kinase Inhibitors Small Molecule Libraries
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Misunderstandings Regarding Sampling and the Role of Statistics in AI.

Journal of chemical information and modeling Sep 23, 2024
Efforts in Artificial Intelligence (AI) to mimic human thinking often seem unbound. Therefore, creating proper guardrails in this context is the responsibility of the collective scientific community. Missteps in this process are inevitable. This View...
Artificial Intelligence Statistics as Topic
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