<i>De Novo</i> Drug Design of Targeted Chemical Libraries Based on Artificial Intelligence and Pair-Based Multiobjective Optimization حسب Alberga Domenico (9356272)

"…In the present study, we conceived a novel pair-based multiobjective approach implemented in an adapted SMILES generative algorithm based on recurrent neural networks for the automated <i>de novo</i> design of new molecules whose overall features are optimized by finding the best trade-offs among relevant physicochemical properties (MW, logP, HBA, HBD) and additional similarity-based constraints biasing specific biological targets. …"

RosettaAMRLD: A Reaction-Driven Approach for Structure-Based Drug Design from Combinatorial Libraries with Monte Carlo Metropolis Algorithms حسب Yidan Tang (6623693)

"…The Rosetta automated Monte Carlo reaction-based ligand design (RosettaAMRLD) integrates a Monte Carlo Metropolis (MCM) algorithm and reaction-driven molecule proposal to enhance structure-based <i>de novo</i> drug discovery. …"

Process of multi angle facial feature point detection algorithm (The character in the Figure is the first author, with her own consent). حسب Shuangyan Li (502833)

Table5_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.XLSX حسب Ali Mostafa Anwar (7454504)

"…For instance, generated S_ij weights were optimized based on gene expression in Saccharomyces cerevisiae, which is expected to vary among different species. …"

Image2_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.PNG حسب Ali Mostafa Anwar (7454504)

"…For instance, generated S_ij weights were optimized based on gene expression in Saccharomyces cerevisiae, which is expected to vary among different species. …"

Table1_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.XLSX حسب Ali Mostafa Anwar (7454504)

"…For instance, generated S_ij weights were optimized based on gene expression in Saccharomyces cerevisiae, which is expected to vary among different species. …"

Image1_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.PNG حسب Ali Mostafa Anwar (7454504)

"…For instance, generated S_ij weights were optimized based on gene expression in Saccharomyces cerevisiae, which is expected to vary among different species. …"

Image3_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.PNG حسب Ali Mostafa Anwar (7454504)

"…For instance, generated S_ij weights were optimized based on gene expression in Saccharomyces cerevisiae, which is expected to vary among different species. …"

Table3_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.XLSX حسب Ali Mostafa Anwar (7454504)

"…For instance, generated S_ij weights were optimized based on gene expression in Saccharomyces cerevisiae, which is expected to vary among different species. …"

Table4_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.XLSX حسب Ali Mostafa Anwar (7454504)

"…For instance, generated S_ij weights were optimized based on gene expression in Saccharomyces cerevisiae, which is expected to vary among different species. …"

Table2_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.XLSX حسب Ali Mostafa Anwar (7454504)

"…For instance, generated S_ij weights were optimized based on gene expression in Saccharomyces cerevisiae, which is expected to vary among different species. …"

Image4_gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.PNG حسب Ali Mostafa Anwar (7454504)

"…For instance, generated S_ij weights were optimized based on gene expression in Saccharomyces cerevisiae, which is expected to vary among different species. …"

Image 1_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.tif حسب Xuehui Fan (10762662)

Data Sheet 7_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx حسب Xuehui Fan (10762662)

Data Sheet 2_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx حسب Xuehui Fan (10762662)

Data Sheet 9_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.xlsx حسب Xuehui Fan (10762662)

Data Sheet 5_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx حسب Xuehui Fan (10762662)

Data Sheet 8_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx حسب Xuehui Fan (10762662)

Data Sheet 6_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx حسب Xuehui Fan (10762662)

Data Sheet 1_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx حسب Xuehui Fan (10762662)