Machine Learning in Chemistry
Machine Learning in Chemistry @ML_Chem ·
Deep Learning Enables Pixel-Level Nanoparticle Distribution Mapping in Routine Histological Sections by Integrating Cancer Associated Fibroblasts Features #machinelearning #compchem pubs.acs.org/doi/abs/10.102…
Deep Learning Enables Pixel-Level Nanoparticle Distribution Mapping in Routine Histological...

The efficient accumulation and uniform distribution of nanomedicine within tumors are critical for achieving therapeutic outcomes. However, conventional medical imaging technologies struggle to...

From pubs.acs.org
58
Machine Learning in Chemistry
Machine Learning in Chemistry @ML_Chem ·
Database of Chemicals for Organophosphorus (DCOP): An Information Application Platform for Organophosphorus Compounds #machinelearning #compchem pubs.acs.org/doi/abs/10.102…
Database of Chemicals for Organophosphorus (DCOP): An Information Application Platform for Organo...

Organophosphorus compounds (OPCs) are widely applied in diverse industries, yet their continuous release across the full life cycle poses significant risks to human health and ecosystems. Current...

From pubs.acs.org
96
Machine Learning in Chemistry
Machine Learning in Chemistry @ML_Chem ·
Driving In Vivo Multienzyme Cascades Forward: Regulatory Strategies for Enhanced Biocatalysis #machinelearning #compchem pubs.acs.org/doi/abs/10.102…
Driving In Vivo Multienzyme Cascades Forward: Regulatory Strategies for Enhanced Biocatalysis

In vivo multiple-enzyme cascades have attracted considerable interest for their ability to provide a native microenvironment that supports enzymatic activity and membrane protein function. This...

From pubs.acs.org
122
Machine Learning in Chemistry
Machine Learning in Chemistry @ML_Chem ·
Photoelectrocatalytic Chemical Pathways in Photoassisted Lithium–Sulfur Batteries via a Multiscale Graph-Based Machine Learning Framework #machinelearning #compchem pubs.acs.org/doi/abs/10.102…
Photoelectrocatalytic Chemical Pathways in Photoassisted Lithium–Sulfur Batteries via a Multiscale...

The rapid advancement of photorechargeable batteries is driven by the need for efficient solar energy utilization, with photoassisted lithium–sulfur batteries (PALSBs) emerging as strong contenders...

From pubs.acs.org
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115
JCIM & JCTC Journals
JCIM & JCTC Journals @JCIM_JCTC ·
Mechanism of Polyester Hydrolysis by Marine Bacterium PE-H Enzyme: an Atomistic and Thermodynamic Characterization #MolecularDynamics pubs.acs.org/doi/10.1021/ac… #JCIM Vol66 Issue4 #compchem
Mechanism of Polyester Hydrolysis by Marine Bacterium PE-H Enzyme: an Atomistic and Thermodynamic...

Polyethylene terephthalate (PET) is a widely used plastic due to its durability and adaptability; however, its resistance to natural degradation has led to severe accumulation in the environment....

From pubs.acs.org
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216
Machine Learning in Chemistry
Machine Learning in Chemistry @ML_Chem ·
Long‐Tea‐CLIP: An Expert‐Level Multimodal AI Framework for Fine‐Grained Green Tea Grading Across Five Sensory Dimensions #machinelearning #compchem advanced.onlinelibrary.wiley.com/doi/10.1002/ad…
Long‐Tea‐CLIP: An Expert‐Level Multimodal AI Framework for Fine‐Grained Green Tea Grading Across...

Long-Tea-CLIP (Contrastive Language-Image Pre-training) presents a multimodal AI framework that integrates visual, metabolomic, and sensory knowledge to grade green tea across appearance, soup...

From advanced.onlinelibrary.wiley.com
157
Machine Learning in Chemistry
Machine Learning in Chemistry @ML_Chem ·
Dual-Metal Doping Nanostructures for Sensitive Detection of Hydrogen Sulfide Gas under High Humidity #machinelearning #compchem pubs.acs.org/doi/abs/10.102…
Dual-Metal Doping Nanostructures for Sensitive Detection of Hydrogen Sulfide Gas under High Humidity

A key challenge in hydrogen sulfide (H2S) detection is developing gas sensors that concurrently achieve high sensitivity, excellent selectivity, and low-cost fabrication, critical for industrial...

From pubs.acs.org
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193
JCIM & JCTC Journals
JCIM & JCTC Journals @JCIM_JCTC ·
A Novel Metabolic Pathway Design Method Based on Evolutionary Algorithms and Metabolic Network Evaluation pubs.acs.org/doi/10.1021/ac… #JCIM Vol66 Issue4 #compchem
A Novel Metabolic Pathway Design Method Based on Evolutionary Algorithms and Metabolic Network...

Metabolic pathway design is a fundamental aspect of metabolic engineering, playing a crucial role in the microbial synthesis of high-value compounds. While metabolic engineers recognize the prevale...

From pubs.acs.org
233
Machine Learning in Chemistry
Machine Learning in Chemistry @ML_Chem ·
Integrating Molecular Dynamics and Deep Learning to Elucidate Conformational Plasticity Underlying the Reduced Activity of Glycocin F #machinelearning #compchem pubs.acs.org/doi/abs/10.102…
Integrating Molecular Dynamics and Deep Learning to Elucidate Conformational Plasticity Underlying...

The escalating crisis of multidrug-resistant bacteria demands a new generation of antibiotics. Glycocin F (GccF), a potent bacteriocin, is a promising candidate, but its function hinges on unique...

From pubs.acs.org
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4
815
Machine Learning in Chemistry
Machine Learning in Chemistry @ML_Chem ·
AI-Driven Species Sensitivity Distribution (AI-4-SSD) Framework for Predicting Aquatic Ecological Risks of Chemical Pollutants in Global Near-Coastal Environments #machinelearning #compchem pubs.acs.org/doi/abs/10.102…
AI-Driven Species Sensitivity Distribution (AI-4-SSD) Framework for Predicting Aquatic Ecological...

Currently, more than 350,000 chemicals and chemical mixtures have been registered for global production and use, and they are inevitably released into global near-coastal environments during their...

From pubs.acs.org
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133
Machine Learning in Chemistry
Machine Learning in Chemistry @ML_Chem ·
Spatially Optimized Nutrient Management as a Climate-Resilient Strategy to Reduce Nitrogen Runoff from Global Croplands #machinelearning #compchem pubs.acs.org/doi/abs/10.102…
Spatially Optimized Nutrient Management as a Climate-Resilient Strategy to Reduce Nitrogen Runoff...

Nitrogen fertilizer, as an indispensable input in crop production, has played a crucial role in enhancing crop yields. However, the associated cropland nitrogen runoff has significantly intensified...

From pubs.acs.org
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132
Machine Learning in Chemistry
Machine Learning in Chemistry @ML_Chem ·
Shapley Additive exPlanations-Integrated Convolutional Neural Networks for Chemically Interpretable Fourier-Transform Infrared-Based Microplastic Characterization #machinelearning #compchem pubs.acs.org/doi/abs/10.102…
Shapley Additive exPlanations-Integrated Convolutional Neural Networks for Chemically Interpretable...

Fourier-transform infrared (FTIR) spectroscopy is a widely adopted technique for microplastic (MP) identification due to its molecular sensitivity and nondestructive nature. However, many FTIR–mach...

From pubs.acs.org
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204
Machine Learning in Chemistry
Machine Learning in Chemistry @ML_Chem ·
A machine-learning framework for interpretable prediction of cellulose degree of polymerization retention in green solvents #machinelearning #compchem pubs.rsc.org/en/Content/Art…
A machine-learning framework for interpretable prediction of cellulose degree of polymerization...

Cellulose is one of the most abundant natural renewable polymers. Its wide availability, biocompatibility, and biodegradability enable broad applications in papermaking, textiles, biomedical materi...

From pubs.rsc.org
162
JCIM & JCTC Journals
JCIM & JCTC Journals @JCIM_JCTC ·
Natural Product-like Fragments Unlock Novel Chemotypes for a Kinase Target─Exploring Options beyond the Flatland pubs.acs.org/doi/10.1021/ac… @CzodrowskiPaul #JCIM Vol66 Issue4 #compchem
Natural Product-like Fragments Unlock Novel Chemotypes for a Kinase Target─Exploring Options beyond...

In this study, we utilized a high-performance soaking system of protein kinase A (PKA) to perform a crystallographic screening of a natural product-like fragment library. We resolved 36 fragment-bo...

From pubs.acs.org
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715
Machine Learning in Chemistry
Machine Learning in Chemistry @ML_Chem ·
Can You Help ChatGPT Get an “A” in Organic Chemistry? Teaching Effective Prompting of Large Language Models for Reaction Prediction #machinelearning #compchem pubs.acs.org/doi/abs/10.102…
Can You Help ChatGPT Get an “A” in Organic Chemistry? Teaching Effective Prompting of Large...

As generative artificial intelligence (AI) tools such as large language models (LLMs) become widespread, they are increasingly finding applications in chemical sciences. Although LLMs have achieved...

From pubs.acs.org
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