AIMC Topic: Machine Learning

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Machine learning enabled protein secondary structure characterization using drop-coating deposition Raman spectroscopy.

Journal of pharmaceutical and biomedical analysis Jul 15, 2025
Protein structure characterization is critical for therapeutic protein drug development and production. Drop-coating deposition Raman (DCDR) spectroscopy offers rapid and cost-effective acquisition of vibrational spectral data characteristic of prote...
Least-Squares Analysis Protein Structure, Secondary Machine Learning Algorithms Spectrum Analysis, Raman Proteins
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Metabolomic machine learning predictor for arsenic-associated hypertension risk in male workers.

Journal of pharmaceutical and biomedical analysis Jul 15, 2025
Arsenic (As)-induced hypertension is a significant public health concern, highlighting the need for early risk prediction. This study aimed to develop a predictive model for occupational As exposure and hypertension using metabolomics and machine lea...
Occupational Diseases Blood Pressure Arsenic Male Hypertension Middle Aged Humans Metabolomics Risk Factors ROC Curve Adult Occupational Exposure Machine Learning
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Enhancing Drug-Target Interaction Prediction through Transfer Learning from Activity Cliff Prediction Tasks.

Journal of chemical information and modeling Jul 14, 2025
Recently, machine learning (ML) has gained popularity in the early stages of drug discovery. This trend is unsurprising given the increasing volume of relevant experimental data and the continuous improvement of ML algorithms. However, conventional m...
Proteins Pharmaceutical Preparations Machine Learning Drug Discovery
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A Diagnosis-Based Siamese Network for Fault Detection Through Transfer Learning.

Journal of chemical information and modeling Jul 14, 2025
Traditional deep-learning-based approaches often struggle with data imbalance and variability across fault conditions and normal scenarios, especially in industrial processes. Besides, inconsistent feature distributions from combining different fault...
Algorithms Deep Learning Neural Networks, Computer Machine Learning
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Assessing Uncertainty in Machine Learning for Polymer Property Prediction: A Benchmark Study.

Journal of chemical information and modeling Jul 14, 2025
Machine learning (ML) has emerged as a transformative tool in material science, enabling accelerated discovery and design of novel molecules while reducing experimental costs. Uncertainty quantification (UQ) is crucial for enhancing the reliability o...
Polymers Benchmarking Monte Carlo Method Uncertainty Machine Learning Bayes Theorem
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Structural Bias in Three-Dimensional Autoregressive Generative Machine Learning of Organic Molecules.

Journal of chemical information and modeling Jul 14, 2025
A range of generative machine learning models for the design of novel molecules and materials have been proposed in recent years. Models that can generate three-dimensional structures are particularly suitable for quantum chemistry workflows, enablin...
Molecular Structure Machine Learning Organic Chemicals
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Optimizing Vanadium-Catalyzed Epoxidation Reactions: Machine-Learning-Driven Yield Predictions and Data Augmentation.

Journal of chemical information and modeling Jul 14, 2025
Catalytic epoxidations are key chemical processes serving as essential steps in the synthesis of commercially valuable compounds. This study presents an innovative supervised machine learning (ML) model to predict the reaction yield of the vanadium-c...
Epoxy Compounds Alkenes Alcohols Machine Learning Catalysis Vanadium
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Distance-Aware Molecular Property Prediction in Nonlinear Structure-Property Space.

Journal of chemical information and modeling Jul 14, 2025
Molecular property prediction with limited data in novel chemical domains remains challenging. We introduce an approach based on the hypothesis that prediction difficulty increases systematically with distance from well-characterized regions in an ap...
Machine Learning Uncertainty Drug Discovery Nonlinear Dynamics
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Advancing Drug Discovery with Enhanced Chemical Understanding via Asymmetric Contrastive Multimodal Learning.

Journal of chemical information and modeling Jul 14, 2025
The versatility of multimodal deep learning holds tremendous promise for advancing scientific research and practical applications. As this field continues to evolve, the collective power of cross-modal analysis promises to drive transformative innova...
Machine Learning Drug Discovery Deep Learning
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CACHE Challenge #2: Targeting the RNA Site of the SARS-CoV-2 Helicase Nsp13.

Journal of chemical information and modeling Jul 14, 2025
A critical assessment of computational hit-finding experiments (CACHE) challenge was conducted to predict ligands for the SARS-CoV-2 Nsp13 helicase RNA binding site, a highly conserved COVID-19 target. Twenty-three participating teams comprised of co...
Binding Sites RNA Helicases Machine Learning COVID-19 Ligands SARS-CoV-2 Humans Molecular Docking Simulation COVID-19 Drug Treatment Methyltransferases Protein Binding Drug Discovery Viral Nonstructural Proteins RNA, Viral Antiviral Agents
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