AIMC Journal:
Journal of chemical information and modeling

Showing 341 to 350 of 934 articles

AIRI: Predicting Retention Indices and Their Uncertainties Using Artificial Intelligence.

Journal of chemical information and modeling Jan 17, 2024
The Kováts retention index (RI) is a quantity measured using gas chromatography and is commonly used in the identification of chemical structures. Creating libraries of observed RI values is a laborious task, so we explore the use of a deep neural ne...
Neural Networks, Computer Artificial Intelligence Uncertainty
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Invariant Molecular Representations for Heterogeneous Catalysis.

Journal of chemical information and modeling Jan 10, 2024
Catalyst screening is a critical step in the discovery and development of heterogeneous catalysts, which are vital for a wide range of chemical processes. In recent years, computational catalyst screening, primarily through density functional theory ...
Neural Networks, Computer Machine Learning Animals Cattle Adsorption Catalysis
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HyperPCM: Robust Task-Conditioned Modeling of Drug-Target Interactions.

Journal of chemical information and modeling Jan 7, 2024
A central problem in drug discovery is to identify the interactions between drug-like compounds and protein targets. Over the past few decades, various quantitative structure-activity relationship (QSAR) and proteo-chemometric (PCM) approaches have b...
Neural Networks, Computer Machine Learning Drug Discovery Drug Development Proteins
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Active Learning Approach for Guiding Site-of-Metabolism Measurement and Annotation.

Journal of chemical information and modeling Jan 3, 2024
The ability to determine and predict metabolically labile atom positions in a molecule (also called "sites of metabolism" or "SoMs") is of high interest to the design and optimization of bioactive compounds, such as drugs, agrochemicals, and cosmetic...
Machine Learning Software
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ProSTAGE: Predicting Effects of Mutations on Protein Stability by Using Protein Embeddings and Graph Convolutional Networks.

Journal of chemical information and modeling Jan 2, 2024
Protein thermodynamic stability is essential to clarify the relationships among structure, function, and interaction. Therefore, developing a faster and more accurate method to predict the impact of the mutations on protein stability is helpful for p...
Neural Networks, Computer Proteins Mutation Protein Stability Protein Structure, Secondary
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Chemprop: A Machine Learning Package for Chemical Property Prediction.

Journal of chemical information and modeling Dec 26, 2023
Deep learning has become a powerful and frequently employed tool for the prediction of molecular properties, thus creating a need for open-source and versatile software solutions that can be operated by nonexperts. Among the current approaches, direc...
Neural Networks, Computer Machine Learning Software Water Chemical Phenomena
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AIDDISON: Empowering Drug Discovery with AI/ML and CADD Tools in a Secure, Web-Based SaaS Platform.

Journal of chemical information and modeling Dec 22, 2023
The widespread proliferation of artificial intelligence (AI) and machine learning (ML) methods has a profound effect on the drug discovery process. However, many scientists are reluctant to utilize these powerful tools due to the steep learning curve...
Artificial Intelligence Machine Learning Power, Psychological Molecular Docking Simulation Drug Discovery Internet
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Comprehensive Review of Drug-Drug Interaction Prediction Based on Machine Learning: Current Status, Challenges, and Opportunities.

Journal of chemical information and modeling Dec 22, 2023
Detecting drug-drug interactions (DDIs) is an essential step in drug development and drug administration. Given the shortcomings of current experimental methods, the machine learning (ML) approach has become a reliable alternative, attracting extensi...
Machine Learning Databases, Factual Pharmaceutical Preparations Drug Interactions Knowledge Bases
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Compound Classification and Consideration of Correlation with Chemical Descriptors from Articles on Antioxidant Capacity Using Natural Language Processing.

Journal of chemical information and modeling Dec 20, 2023
In recent times, there has been a substantial increase in the number of articles focusing on antioxidants. However, the development of a comprehensive estimator for antioxidant capacity remains elusive due to the challenge of integrating information ...
Antioxidants Flavonoids Natural Language Processing
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When Yield Prediction Does Not Yield Prediction: An Overview of the Current Challenges.

Journal of chemical information and modeling Dec 20, 2023
Machine Learning (ML) techniques face significant challenges when predicting advanced chemical properties, such as yield, feasibility of chemical synthesis, and optimal reaction conditions. These challenges stem from the high-dimensional nature of th...
Machine Learning Cheminformatics
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