Journal of chemical information and modeling
Jul 17, 2025
Graph Neural Networks (GNNs) are powerful tools for predicting chemical properties, but their black-box nature can limit trust and utility. Explainability through feature attribution and awareness of prediction uncertainty are critical for practical ...
Gas chromatography coupled with electron impact mass spectrometry (GC‑EI‑MS) is a widely used analytical technique for identifying volatile and semi‑volatile compounds in applications ranging from pharmaceutical research to material science. However,...
International journal of biological macromolecules
Mar 24, 2025
The application of machine learning in pullulan biofermentation has demonstrated significant potential. Explainable machine learning enhances model transparency and interpretability by revealing the relationships between variables. In this study, we ...
International journal of biological macromolecules
Mar 16, 2025
This study focuses on optimizing the fermentation process for the production of low molecular weight welan gum (LMW-WG) using Sphingomonas sp. ATCC 31555 with glycerol as the sole carbon source. A series of single-factor experiments were conducted to...
European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology
Dec 17, 2024
PURPOSE: Clostridioides difficile is the main cause of antibiotic related diarrhea and some ribotypes (RT), such as RT027, RT181 or RT078, are considered high risk clones. A fast and reliable approach for C. difficile ribotyping is needed for a corre...
Constructing antifouling surfaces is a crucial technique for optimizing the performance of devices such as water treatment membranes and medical devices in practical environments. These surfaces are achieved by modification with hydrophilic polymers....
Linear prediction models based on data with large inhomogeneity or abrupt non-linearities often perform poorly because relationships between groups in the data dominate the model. Given that the data is locally linear, this can be overcome by splitti...
INTRODUCTION: Protein-protein interactions (PPIs) have been often considered undruggable targets although they are attractive for the discovery of new therapeutics. The spread of artificial intelligence and machine learning complemented with experime...
In the process of converting food-processing by-products to value-added ingredients, fine grained control of the raw materials, enzymes and process conditions ensures the best possible yield and economic return. However, when raw material batches lac...
There are more amino acid permutations within a 40-residue sequence than atoms on Earth. This vast chemical search space hinders the use of human learning to design functional polymers. Here we show how machine learning enables the de novo design of ...
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