Modeling and Change Detection for Count-Weighted Multilayer Networks حسب Hang Dong (406485)

"…<p>In a typical network with a set of individuals, it is common to have multiple types of interactions between two individuals. …"

Comparison of network representation formats. حسب Giuseppe Agapito (104634)

"…This manuscript presents a comprehensive overview of NA methodologies, including the importance of preprocessing network data, selecting suitable input formats, and understanding diverse network types such as attributed, temporal, and multilayer networks. …"

Schematic representation of data processing and analysis. حسب Yang Zhang (30734)

"…Icon 2 shows the feature selection process, which includes XGBoost and random forest algorithms. Icon 3 indicates calculation of the MIC value for every two nodes in the network, which represents the interaction between nodes. …"

Key aspects of network alignment documentation. حسب Giuseppe Agapito (104634)

"…This manuscript presents a comprehensive overview of NA methodologies, including the importance of preprocessing network data, selecting suitable input formats, and understanding diverse network types such as attributed, temporal, and multilayer networks. …"

Dataset and code used in the temporal seed dispersal multilayer network Costa et al. 2020 Journal of Ecology حسب José Costa (8567610)

"…<p>Dataset and code supporting the results from Costa et al. (2020) Species temporal persistence promotes the stability of fruit-frugivore interactions across a five-year multilayer network, Journal of Ecology.…"

Table_1_Biased Random Walk With Restart on Multilayer Heterogeneous Networks for MiRNA–Disease Association Prediction.XLSX حسب Jia Qu (28271)

"…Here, based on heterogeneous networks built on the information of known miRNA–disease associations, miRNA function similarity, disease semantic similarity, and Gaussian interaction profile kernel similarity for miRNAs and diseases, we developed a computing model of biased random walk with restart on multilayer heterogeneous networks for miRNA–disease association prediction (BRWRMHMDA) through enforcing degree-based biased random walk with restart (BRWR). …"

Heatmap clustering of the interactions effects among the three chemical fertilizers including N (0, 100, and 200 g), K (0, 100, 200, and 300 g), and Mg (0, 50, and 100 g) on fruit... حسب Mahmoud Reza Ramezanpour (12085852)

Comparison of seed node selection methods. حسب Giuseppe Agapito (104634)

"…This manuscript presents a comprehensive overview of NA methodologies, including the importance of preprocessing network data, selecting suitable input formats, and understanding diverse network types such as attributed, temporal, and multilayer networks. …"

Table1_Innovation in the Breeding of Common Bean Through a Combined Approach of in vitro Regeneration and Machine Learning Algorithms.docx حسب Muhammad Aasim (3666946)

"…In this study, the establishment of efficient and reproducible in vitro regeneration followed by predicting and optimizing through machine learning (ML) models, such as artificial neural network algorithms, was performed. Mature embryos of common bean were pretreated with 5, 10, and 20 mg/L benzylaminopurine (BAP) for 20 days followed by isolation of plumular apice for in vitro regeneration and cultured on a post-treatment medium containing 0.25, 0.50, 1.0, and 1.50 mg/L BAP for 8 weeks. …"

Table2_Innovation in the Breeding of Common Bean Through a Combined Approach of in vitro Regeneration and Machine Learning Algorithms.docx حسب Muhammad Aasim (3666946)

"…In this study, the establishment of efficient and reproducible in vitro regeneration followed by predicting and optimizing through machine learning (ML) models, such as artificial neural network algorithms, was performed. Mature embryos of common bean were pretreated with 5, 10, and 20 mg/L benzylaminopurine (BAP) for 20 days followed by isolation of plumular apice for in vitro regeneration and cultured on a post-treatment medium containing 0.25, 0.50, 1.0, and 1.50 mg/L BAP for 8 weeks. …"

Data_Sheet_1_An Ensemble Approach to Predict Schizophrenia Using Protein Data in the N-methyl-D-Aspartate Receptor (NMDAR) and Tryptophan Catabolic Pathways.PDF حسب Eugene Lin (759907)

"…We compared our ensemble boosting framework with other state-of-the-art algorithms such as support vector machine, multilayer feedforward neural networks, logistic regression, random forests, naive Bayes, and C4.5 decision tree. …"

DataSheet1_Network-based integrative multi-omics approach reveals biosignatures specific to COVID-19 disease phases.zip حسب Francis E. Agamah (11609831)

"…Disease-state specific omics-graphs were constructed by integrating multi-omics data with the unified COVID-19 knowledge graph. We expanded on the network layers of multiXrank, a random walk with restart on multilayer network algorithm, to explore disease state omics-specific graphs and perform enrichment analysis.…"

MAE, R-squared, RMSE & SMAPE of the final model. حسب Gayatree Nayak (15426871)

"…The results revealed that the most suited model was multilayer-feed-forward neural networks with an R² value of 0.93. …"

Regression test. حسب Gayatree Nayak (15426871)

"…The results revealed that the most suited model was multilayer-feed-forward neural networks with an R² value of 0.93. …"

Flow diagram of the study. حسب Gayatree Nayak (15426871)

"…The results revealed that the most suited model was multilayer-feed-forward neural networks with an R² value of 0.93. …"

Relative importance of factors. حسب Gayatree Nayak (15426871)

"…The results revealed that the most suited model was multilayer-feed-forward neural networks with an R² value of 0.93. …"

Standard deviation of predictors. حسب Gayatree Nayak (15426871)

"…The results revealed that the most suited model was multilayer-feed-forward neural networks with an R² value of 0.93. …"

Demystifying artificial intelligence and deep learning in dentistry حسب Jonas Almeida RODRIGUES (6048392)

"…CNN algorithms allow to perform tasks like image classification, object detection and segmentation. …"

Data_Sheet_1_Computational Characteristics of the Striatal Dopamine System Described by Reinforcement Learning With Fast Generalization.PDF حسب Yoshihisa Fujita (9154691)

"…We proposed a novel reinforcement learning model with multilayer neural networks in which the synaptic weights of only the last layer are updated according to the prediction error. …"

Image_3_Genomic prediction for sugarcane diseases including hybrid Bayesian-machine learning approaches.jpeg حسب Chensong Chen (18475374)

"…These algorithms were: Genomic best linear unbiased prediction (GBLUP), including extensions to model dominance and epistasis, Bayesian methods including BayesC and BayesR, Machine learning methods including random forest, multilayer perceptron (MLP), modified convolutional neural network (CNN) and attention networks designed to capture epistasis across the genome-wide markers. …"