بدائل البحث:
model optimization » codon optimization (توسيع البحث), global optimization (توسيع البحث), wolf optimization (توسيع البحث)
library based » laboratory based (توسيع البحث)
binary basic » binary mask (توسيع البحث)
based robust » based probes (توسيع البحث)
basic model » based model (توسيع البحث), base model (توسيع البحث), bapc model (توسيع البحث)
model optimization » codon optimization (توسيع البحث), global optimization (توسيع البحث), wolf optimization (توسيع البحث)
library based » laboratory based (توسيع البحث)
binary basic » binary mask (توسيع البحث)
based robust » based probes (توسيع البحث)
basic model » based model (توسيع البحث), base model (توسيع البحث), bapc model (توسيع البحث)
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1
Fine-Tuning a Genetic Algorithm for CAMD: A Screening-Guided Warm Start
منشور في 2025"…In response to these challenges, this work presents a method to fine-tune a genetic algorithm for CAMD. The proposed method builds on the COSMO-CAMD framework that utilizes a genetic algorithm for solving optimization-based molecular design problems and COSMO-RS for predicting physical properties of molecules. …"
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2
Fine-Tuning a Genetic Algorithm for CAMD: A Screening-Guided Warm Start
منشور في 2025"…In response to these challenges, this work presents a method to fine-tune a genetic algorithm for CAMD. The proposed method builds on the COSMO-CAMD framework that utilizes a genetic algorithm for solving optimization-based molecular design problems and COSMO-RS for predicting physical properties of molecules. …"
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3
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4
Predictive Analysis of Mushroom Toxicity Based Exclusively on Their Natural Habitat.
منشور في 2025"…Model evaluation was based on accuracy metrics and qualitative analysis of the confusion matrix.. …"
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5
Code
منشور في 2025"…</p><p><br></p><p dir="ltr">This architecture was implemented using the PyTorch library and trained using cross-entropy loss. The model was optimized to classify RNA sequences, achieving robust performance across multiple test sets.…"
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6
Core data
منشور في 2025"…</p><p><br></p><p dir="ltr">This architecture was implemented using the PyTorch library and trained using cross-entropy loss. The model was optimized to classify RNA sequences, achieving robust performance across multiple test sets.…"