Computational Intelligence in Protein-Ligand Interaction Analysis
portes grátis
Computational Intelligence in Protein-Ligand Interaction Analysis
Zhang, Jun; Wang, Bing; Chen, Peng
Elsevier Science Publishing Co Inc
03/2024
278
Mole
Inglês
9780128243862
15 a 20 dias
Descrição não disponível.
1. Computational intelligence methods in protein-ligand interactions
2. Random forest method for predicting protein ligand-binding residues
3. Encoders of protein residues for identifying protein-protein interacting residues
4. Identification of hot spot residues in protein interfaces from protein sequences and ensemble methods
5. Semi-supervised prediction of protein interaction sites from unlabeled sample information
6. Developing computational model to predict protein-protein interaction sites based on XGBoost algorithm
7. Evolutional algorithms and their applications in protein long-range contact prediction
8. A novel robust geometric approach for modelling protein-protein interaction networks
9. Prediction of protein-protein interactions from amino acid sequences with ensemble extreme learning machines and principal component analysis
10. Ensemble learning-based prediction on drug-target interactions
11. Convolutional neural networks for drug-target interaction prediction
12. Ensemble learning methods for drug-induced liver injury identification
13. Database construction for mutant protein interactions
14. A linear programming computational framework integrates phosphor-proteomics and prior knowledge to predict drug efficacy
2. Random forest method for predicting protein ligand-binding residues
3. Encoders of protein residues for identifying protein-protein interacting residues
4. Identification of hot spot residues in protein interfaces from protein sequences and ensemble methods
5. Semi-supervised prediction of protein interaction sites from unlabeled sample information
6. Developing computational model to predict protein-protein interaction sites based on XGBoost algorithm
7. Evolutional algorithms and their applications in protein long-range contact prediction
8. A novel robust geometric approach for modelling protein-protein interaction networks
9. Prediction of protein-protein interactions from amino acid sequences with ensemble extreme learning machines and principal component analysis
10. Ensemble learning-based prediction on drug-target interactions
11. Convolutional neural networks for drug-target interaction prediction
12. Ensemble learning methods for drug-induced liver injury identification
13. Database construction for mutant protein interactions
14. A linear programming computational framework integrates phosphor-proteomics and prior knowledge to predict drug efficacy
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Prediction; ligand-binding; random forest method; protein; encoders; interaction prediction; machine-based; XGBoost; algorithms; dataset; data; evolution; long-range contact prediction; t-logistic semantic embedding; t-LSE; PPI; component analysis; amino acid sequence; drug-target interactions; neural network; convolutional; liver injury identification; mutant protein; phosphor-proteomics; drug efficacy; Ternary status based Integer Linear Programming; TILP; mass spectrometry; transformation; visualization; macromolecules; GMSSTF; general molecular skin surface transformation framework; optimization
1. Computational intelligence methods in protein-ligand interactions
2. Random forest method for predicting protein ligand-binding residues
3. Encoders of protein residues for identifying protein-protein interacting residues
4. Identification of hot spot residues in protein interfaces from protein sequences and ensemble methods
5. Semi-supervised prediction of protein interaction sites from unlabeled sample information
6. Developing computational model to predict protein-protein interaction sites based on XGBoost algorithm
7. Evolutional algorithms and their applications in protein long-range contact prediction
8. A novel robust geometric approach for modelling protein-protein interaction networks
9. Prediction of protein-protein interactions from amino acid sequences with ensemble extreme learning machines and principal component analysis
10. Ensemble learning-based prediction on drug-target interactions
11. Convolutional neural networks for drug-target interaction prediction
12. Ensemble learning methods for drug-induced liver injury identification
13. Database construction for mutant protein interactions
14. A linear programming computational framework integrates phosphor-proteomics and prior knowledge to predict drug efficacy
2. Random forest method for predicting protein ligand-binding residues
3. Encoders of protein residues for identifying protein-protein interacting residues
4. Identification of hot spot residues in protein interfaces from protein sequences and ensemble methods
5. Semi-supervised prediction of protein interaction sites from unlabeled sample information
6. Developing computational model to predict protein-protein interaction sites based on XGBoost algorithm
7. Evolutional algorithms and their applications in protein long-range contact prediction
8. A novel robust geometric approach for modelling protein-protein interaction networks
9. Prediction of protein-protein interactions from amino acid sequences with ensemble extreme learning machines and principal component analysis
10. Ensemble learning-based prediction on drug-target interactions
11. Convolutional neural networks for drug-target interaction prediction
12. Ensemble learning methods for drug-induced liver injury identification
13. Database construction for mutant protein interactions
14. A linear programming computational framework integrates phosphor-proteomics and prior knowledge to predict drug efficacy
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Prediction; ligand-binding; random forest method; protein; encoders; interaction prediction; machine-based; XGBoost; algorithms; dataset; data; evolution; long-range contact prediction; t-logistic semantic embedding; t-LSE; PPI; component analysis; amino acid sequence; drug-target interactions; neural network; convolutional; liver injury identification; mutant protein; phosphor-proteomics; drug efficacy; Ternary status based Integer Linear Programming; TILP; mass spectrometry; transformation; visualization; macromolecules; GMSSTF; general molecular skin surface transformation framework; optimization
