Results 101 to 110 of about 9,740,987 (348)
Keyword Data Analysis Using Bayesian Conjugate Prior Distribution [PDF]
, 2020 Sunghae Jun
openalex +1 more source
Mechanism‐Driven Screening of Membrane‐Targeting and Pore‐Forming Antimicrobial Peptides
Advanced Science, EarlyView.To combat antibiotic resistance, this study employs mechanism‐driven screening with machine learning to identify pore‐forming antimicrobial peptides from amphibian and human metaproteomes. Seven peptides are validated, showing minimal toxicity and membrane disruption.
Jiaxuan Li +9 more
wiley +1 more source
Advanced Science, EarlyView.This study constructed the first D‐amino acid antimicrobial peptide dataset and developed an AI model for efficient screening of substitution sites, with 80% of candidate peptides showing enhanced activity. The lead peptide dR2‐1 demonstrated potent antimicrobial activity in vitro and in vivo, high stability, and low toxicity.
Yinuo Zhao +14 more
wiley +1 more source
Advanced Science, EarlyView.Microbial synthesis of nanomaterials (NMs) is eco‐friendly, but the screening of microorganisms is limited by inefficient traditional methods (currently only involving∽400 microorganisms/90 NMs). We propose AI framework MicrobeDiscover, integrating a knowledge graph of microbe‐NM interactions.
Ludi Wang +12 more
wiley +1 more source
Advanced Science, EarlyView.This review comprehensively summarizes the atomic defects in TMDs for their applications in sustainable energy storage devices, along with the latest progress in ML methodologies for high‐throughput TEM data analysis, offering insights on how ML‐empowered microscopy facilitates bridging structure–property correlation and inspires knowledge for precise ...
Zheng Luo +6 more
wiley +1 more source
Title, abstract, keywords, and authorship criteria
Kerala Journal of OphthalmologyIn the domain of medical research, the importance of developing precise and informative elements such as the title, abstract, keywords, and authorship criteria cannot be overstated.
M V Sruthi
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High‐Conductivity Electrolytes Screened Using Fragment‐ and Composition‐Aware Deep Learning
Advanced Science, EarlyView.We present a new deep learning framework that hierarchically links molecular and functional unit attributions to predict electrolyte conductivity. By integrating molecular composition, ratios, and physicochemical descriptors, it achieves accurate, interpretable predictions and large‐scale virtual screening, offering chemically meaningful insights for ...
Xiangwen Wang +6 more
wiley +1 more source
How AI Shapes the Future Landscape of Sustainable Building Design With Climate Change Challenges?
Advanced Science, EarlyView.This review examines how artificial intelligence reshapes sustainable building design faced with climate change challenges. The authors synthesize existing studies to demonstrate AI's transformative potential across design lifecycle phases from climate‐aware form generation to performance optimization.
Pengyuan Shen +5 more
wiley +1 more source