AI Medical Compendium Journal:
Journal of chemical information and modeling

Showing 31 to 40 of 934 articles

A Database for Large-Scale Docking and Experimental Results.

Journal of chemical information and modeling Apr 24, 2025
The rapid expansion of readily accessible compounds over the past six years has transformed molecular docking, improving hit rates and affinities. While many millions of molecules may score well in a docking campaign, the results are rarely fully sha...
Machine Learning Databases, Factual Molecular Docking Simulation Proteins Ligands Small Molecule Libraries
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COLOR: A Compositional Linear Operation-Based Representation of Protein Sequences for Identification of Monomer Contributions to Properties.

Journal of chemical information and modeling Apr 24, 2025
The properties of biological materials like proteins and nucleic acids are largely determined by their primary sequence. Certain segments in the sequence strongly influence specific functions, but identifying these segments, or so-called motifs, is c...
Deep Learning Proteins Amino Acid Sequence
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KNDM: A Knowledge Graph Transformer and Node Category Sensitive Contrastive Learning Model for Drug and Microbe Association Prediction.

Journal of chemical information and modeling Apr 23, 2025
It has been proven that the microbiome in human bodies can promote or inhibit the treatment effects of the drugs by affecting their toxicities and activities. Therefore, identifying drug-related microbes helps in understanding how drugs exert their f...
Humans Machine Learning Microbiota
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Unraveling Disease-Associated PIWI-Interacting RNAs with a Contrastive Learning Methods.

Journal of chemical information and modeling Apr 22, 2025
PIWI-interacting RNAs (piRNAs) are a class of small, non-coding RNAs predominantly expressed in the germ cells of animals and play a crucial role in maintaining genomic integrity, mediating transposon suppression, and ensuring gene stability. Beyond ...
Humans Machine Learning Computational Biology RNA, Small Interfering
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Modeling Chemical Reaction Networks Using Neural Ordinary Differential Equations.

Journal of chemical information and modeling Apr 22, 2025
In chemical reaction network theory, ordinary differential equations are used to model the temporal change of chemical species concentration. As the functional form of these ordinary differential equation systems is derived from an empirical model of...
Neural Networks, Computer Deep Learning Models, Chemical
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Ligand-Based Drug Discovery Leveraging State-of-the-Art Machine Learning Methodologies Exemplified by Cdr1 Inhibitor Prediction.

Journal of chemical information and modeling Apr 16, 2025
Artificial intelligence (AI) is revolutionizing drug discovery with unprecedented speed and efficiency. In computer-aided drug design, structure-based and ligand-based methodologies are the main driving forces for innovation. In cases where no experi...
Humans Machine Learning Drug Discovery Bayes Theorem Ligands
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Improved Solubility Predictions in scCO Using Thermodynamics-Informed Machine Learning Models.

Journal of chemical information and modeling Apr 15, 2025
Accurate solubility prediction in supercritical carbon dioxide (scCO) is crucial for optimizing experimental design by eliminating unnecessary and costly trials at an early stage, thereby streamlining the workflow. A comprehensive solubility database...
Machine Learning Carbon Dioxide Solubility Thermodynamics
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Addressing Imbalanced Classification Problems in Drug Discovery and Development Using Random Forest, Support Vector Machine, AutoGluon-Tabular, and H2O AutoML.

Journal of chemical information and modeling Apr 15, 2025
The classification models built on class imbalanced data sets tend to prioritize the accuracy of the majority class, and thus, the minority class generally has a higher misclassification rate. Different techniques are available to address the class i...
Machine Learning Algorithms Drug Discovery Drug Development Support Vector Machine Random Forest
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Topology-Enhanced Machine Learning Model (Top-ML) for Anticancer Peptide Prediction.

Journal of chemical information and modeling Apr 14, 2025
Recently, therapeutic peptides have demonstrated great promise for cancer treatment. To explore powerful anticancer peptides, artificial intelligence (AI)-based approaches have been developed to systematically screen potential candidates. However, th...
Humans Machine Learning Peptides Antineoplastic Agents
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Machine Learning and Structural Dynamics-Based Approach to Reveal Molecular Mechanism of PTEN Missense Mutations Shared by Cancer and Autism Spectrum Disorder.

Journal of chemical information and modeling Apr 14, 2025
Missense mutations in oncogenic proteins that are concurrently associated with neurodevelopmental disorders have garnered significant attention. Phosphatase and tensin homologue (PTEN) serves as a paradigmatic model for mapping its mutational landsca...
Humans Machine Learning Autism Spectrum Disorder Neoplasms Molecular Dynamics Simulation Protein Conformation Mutation, Missense PTEN Phosphohydrolase
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