Algorithm parameter settings. by Yue Guo (695495)

Pixel ring feature expression. by Guangmei Ma (21432861)

Algorithm performance test results. by Yue Guo (695495)

Experiment 4: Evaluating CPM-based clustering methods on ring-of-cliques networks. by Yasamin Tabatabaee (18095491)

Convergence curve of sparrow search algorithm. by Yue Guo (695495)

Experiment 4: Accuracy of modularity-based consensus clustering methods on ring-of-cliques networks of varying sizes. by Yasamin Tabatabaee (18095491)

Fig 1 - by Mona Selim (12969227)

Table 2_Intelligent grading of sugarcane leaf disease severity by integrating physiological traits with the SSA-XGBoost algorithm.docx by Xinrui Wang (488330)

“…After min-max normalization, six classification models—KNN, AdaBoost, Random Forest (RF), Logistic Regression (LR), Decision Tree (DT), and XGBoost—were developed, and the Sparrow Search Algorithm (SSA) was employed to optimize hyperparameters for enhanced performance.…”

Table 1_Intelligent grading of sugarcane leaf disease severity by integrating physiological traits with the SSA-XGBoost algorithm.xlsx by Xinrui Wang (488330)

“…After min-max normalization, six classification models—KNN, AdaBoost, Random Forest (RF), Logistic Regression (LR), Decision Tree (DT), and XGBoost—were developed, and the Sparrow Search Algorithm (SSA) was employed to optimize hyperparameters for enhanced performance.…”

Genetic codes optimized as a traveling salesman problem - Fig 1 by Oliver Attie (3841450)

Experiment 5: Clustering networks that are only partially clusterable. by Yasamin Tabatabaee (18095491)

DkSP in solving the boundary specification problem. by Xiaochen He (455300)

Folder with all data and algorithms by Jorge Servert Lerdo de Tejada (22290001)

Mitochondrial toxic prediction of marine alga toxins using a predictive model based on feature coupling and ensemble learning algorithms by Guangyin Jia (21075537)

“…By comparing 8 machine learning algorithms and using a weighted soft voting method to integrate the two optimal algorithms, we established 108 prediction models and identified the best ensemble learning model MACCS_LK for screening and defining its application domain. …”

A Multi-Angle Approach to Predict Peptide-GPCR Complexes: The N/OFQ-NOP System as a Successful AlphaFold Application Case Study by Antonella Ciancetta (164206)

“…With nearly 700 structures solved and a growing number of customized structure prediction algorithms being developed at a fast pace, G protein-coupled receptors (GPCRs) are an optimal test case for validating new approaches for the prediction of receptor active state and ligand bioactive conformation complexes. …”

A Multi-Angle Approach to Predict Peptide-GPCR Complexes: The N/OFQ-NOP System as a Successful AlphaFold Application Case Study by Antonella Ciancetta (164206)

“…With nearly 700 structures solved and a growing number of customized structure prediction algorithms being developed at a fast pace, G protein-coupled receptors (GPCRs) are an optimal test case for validating new approaches for the prediction of receptor active state and ligand bioactive conformation complexes. …”

A Multi-Angle Approach to Predict Peptide-GPCR Complexes: The N/OFQ-NOP System as a Successful AlphaFold Application Case Study by Antonella Ciancetta (164206)

“…With nearly 700 structures solved and a growing number of customized structure prediction algorithms being developed at a fast pace, G protein-coupled receptors (GPCRs) are an optimal test case for validating new approaches for the prediction of receptor active state and ligand bioactive conformation complexes. …”

A Multi-Angle Approach to Predict Peptide-GPCR Complexes: The N/OFQ-NOP System as a Successful AlphaFold Application Case Study by Antonella Ciancetta (164206)

“…With nearly 700 structures solved and a growing number of customized structure prediction algorithms being developed at a fast pace, G protein-coupled receptors (GPCRs) are an optimal test case for validating new approaches for the prediction of receptor active state and ligand bioactive conformation complexes. …”

A Multi-Angle Approach to Predict Peptide-GPCR Complexes: The N/OFQ-NOP System as a Successful AlphaFold Application Case Study by Antonella Ciancetta (164206)

“…With nearly 700 structures solved and a growing number of customized structure prediction algorithms being developed at a fast pace, G protein-coupled receptors (GPCRs) are an optimal test case for validating new approaches for the prediction of receptor active state and ligand bioactive conformation complexes. …”

A Multi-Angle Approach to Predict Peptide-GPCR Complexes: The N/OFQ-NOP System as a Successful AlphaFold Application Case Study by Antonella Ciancetta (164206)

“…With nearly 700 structures solved and a growing number of customized structure prediction algorithms being developed at a fast pace, G protein-coupled receptors (GPCRs) are an optimal test case for validating new approaches for the prediction of receptor active state and ligand bioactive conformation complexes. …”