| scholarly article | Q13442814 |
| P8978 | DBLP publication ID | journals/bioinformatics/ChenL05 |
| P356 | DOI | 10.1093/BIOINFORMATICS/BTI721 |
| P8608 | Fatcat ID | release_pxm5v4epybha3p24yolqgd6jwi |
| P698 | PubMed publication ID | 16234318 |
| P5875 | ResearchGate publication ID | 7532777 |
| P2093 | author name string | Mei Liu | |
| Xue-Wen Chen | |||
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| P433 | issue | 24 | |
| P407 | language of work or name | English | Q1860 |
| P921 | main subject | protein-protein interaction | Q896177 |
| P1104 | number of pages | 7 | |
| P304 | page(s) | 4394-4400 | |
| P577 | publication date | 2005-10-18 | |
| P1433 | published in | Bioinformatics | Q4914910 |
| P1476 | title | Prediction of protein-protein interactions using random decision forest framework | |
| P478 | volume | 21 |
| Q47658255 | A Bayesian approach for estimating protein-protein interactions by integrating structural and non-structural biological data |
| Q28276262 | A machine learning approach to predicting protein-ligand binding affinity with applications to molecular docking |
| Q60915322 | A model to predict the function of hypothetical proteins through a nine-point classification scoring schema |
| Q34072505 | A novel feature extraction scheme with ensemble coding for protein-protein interaction prediction |
| Q92584828 | A novel matrix of sequence descriptors for predicting protein-protein interactions from amino acid sequences |
| Q38283868 | A review of in silico approaches for analysis and prediction of HIV-1-human protein-protein interactions |
| Q46137873 | An integrative domain-based approach to predicting protein-protein interactions |
| Q37743545 | Artificial intelligence techniques for colorectal cancer drug metabolism: ontology and complex network. |
| Q33441747 | Assessing reliability of protein-protein interactions by integrative analysis of data in model organisms |
| Q38683274 | Assessing the Potential of Land Use Modification to Mitigate Ambient NO₂ and Its Consequences for Respiratory Health |
| Q51610286 | Automated QSAR with a Hierarchy of Global and Local Models. |
| Q33622920 | Automatic structure classification of small proteins using random forest. |
| Q41870878 | Classifying pairs with trees for supervised biological network inference |
| Q33256165 | Co-evolutionary analysis of domains in interacting proteins reveals insights into domain-domain interactions mediating protein-protein interactions |
| Q33407874 | ComPhy: prokaryotic composite distance phylogenies inferred from whole-genome gene sets |
| Q50321036 | Combination of CRP and NLR: a better predictor of postoperative survival in patients with gastric cancer |
| Q89174572 | Computational Methods for Predicting Protein-Protein Interactions Using Various Protein Features |
| Q41850322 | Computational Prediction of Protein-Protein Interaction Networks: Algo-rithms and Resources |
| Q64988383 | Computational identification of protein-protein interactions in model plant proteomes. |
| Q35104055 | Computational prediction of the human-microbial oral interactome |
| Q39920083 | Critical assessment of sequence-based protein-protein interaction prediction methods that do not require homologous protein sequences |
| Q28754534 | DASMI: exchanging, annotating and assessing molecular interaction data |
| Q33462626 | DASMIweb: online integration, analysis and assessment of distributed protein interaction data |
| Q24610433 | DOMINE: a comprehensive collection of known and predicted domain-domain interactions |
| Q36454332 | DOMINE: a database of protein domain interactions |
| Q29029166 | Deciphering Protein–Protein Interactions. Part II. Computational Methods to Predict Protein and Domain Interaction Partners |
| Q40135840 | Detecting reliable non interacting proteins (NIPs) significantly enhancing the computational prediction of protein-protein interactions using machine learning methods. |
| Q45943660 | Different protein-protein interface patterns predicted by different machine learning methods. |
| Q38266754 | Discovering novel protein-protein interactions by measuring the protein semantic similarity from the biomedical literature |
| Q45944211 | Distributed smoothed tree kernel for protein-protein interaction extraction from the biomedical literature. |
| Q37774003 | Drug discovery and design for complex diseases through QSAR computational methods. |
| Q35380551 | Efficient prediction of progesterone receptor interactome using a support vector machine model |
| Q94596003 | Estimation of soil salt content by combining UAV-borne multispectral sensor and machine learning algorithms |
| Q58697064 | Evolution of In Silico Strategies for Protein-Protein Interaction Drug Discovery |
| Q47643716 | Fast segmentation of kidney components using random forests and ferns |
| Q58649234 | From Experimental Approaches to Computational Techniques: A Review on the Prediction of Protein-Protein Interactions |
| Q33407912 | GAIA: a gram-based interaction analysis tool--an approach for identifying interacting domains in yeast. |
| Q21133651 | Genome-scale screening of drug-target associations relevant to Ki using a chemogenomics approach |
| Q33320137 | Genome-wide inference of protein interaction sites: lessons from the yeast high-quality negative protein-protein interaction dataset |
| Q34461945 | Heterogeneous data integration by tree-augmented naïve Bayes for protein-protein interactions prediction |
| Q28740452 | High-dimensional pharmacogenetic prediction of a continuous trait using machine learning techniques with application to warfarin dose prediction in African Americans |
| Q36051148 | IDDI: integrated domain-domain interaction and protein interaction analysis system |
| Q91827368 | Identification of Targetable Pathways in Oral Cancer Patients via Random Forest and Chemical Informatics |
| Q37316390 | Identification of protein functions using a machine-learning approach based on sequence-derived properties |
| Q46929781 | Identifying subcellular localizations of mammalian protein complexes based on graph theory with a random forest algorithm |
| Q35906379 | Inference of domain-disease associations from domain-protein, protein-disease and disease-disease relationships |
| Q64118560 | Integration of A Deep Learning Classifier with A Random Forest Approach for Predicting Malonylation Sites |
| Q34177262 | Integration strategy is a key step in network-based analysis and dramatically affects network topological properties and inferring outcomes |
| Q93185985 | Inter-Species/Host-Parasite Protein Interaction Predictions Reviewed |
| Q33621912 | Interaction prediction and classification of PDZ domains. |
| Q37364210 | Knowledge-guided inference of domain-domain interactions from incomplete protein-protein interaction networks |
| Q33542870 | Large-scale prediction of protein-protein interactions from structures |
| Q59120488 | Link Prediction Methods and Their Accuracy for Different Social Networks and Network Metrics |
| Q62495870 | Machine Learning-based Virtual Screening and Its Applications to Alzheimer's Drug Discovery: A Review |
| Q90013579 | Machine-learning techniques for the prediction of protein-protein interactions |
| Q33490835 | Multi-level learning: improving the prediction of protein, domain and residue interactions by allowing information flow between levels |
| Q37804514 | Multigenic Modeling of Complex Disease by Random Forests |
| Q41554188 | Multitask learning for host-pathogen protein interactions |
| Q30485904 | Negated bio-events: analysis and identification |
| Q44330643 | On Position-Specific Scoring Matrix for Protein Function Prediction |
| Q38172136 | On protocols and measures for the validation of supervised methods for the inference of biological networks |
| Q36204412 | PPCM: Combing Multiple Classifiers to Improve Protein-Protein Interaction Prediction |
| Q45959110 | PPIevo: protein-protein interaction prediction from PSSM based evolutionary information. |
| Q58737310 | PPInS: a repository of protein-protein interaction sitesbase |
| Q31043905 | Partner-aware prediction of interacting residues in protein-protein complexes from sequence data |
| Q33516895 | Phylogeny-guided interaction mapping in seven eukaryotes |
| Q34109026 | Predicting RNA-protein interactions using only sequence information |
| Q42637434 | Predicting and understanding transcription factor interactions based on sequence level determinants of combinatorial control |
| Q35721356 | Predicting protein-protein interactions based only on sequences information |
| Q33548907 | Predicting protein-protein interactions in unbalanced data using the primary structure of proteins |
| Q34064661 | Predicting residue-residue contacts and helix-helix interactions in transmembrane proteins using an integrative feature-based random forest approach |
| Q33528207 | Predicting the protein-protein interactions using primary structures with predicted protein surface |
| Q30665725 | Predicting whole genome protein interaction networks from primary sequence data in model and non-model organisms using ENTS. |
| Q39541532 | Prediction of Protein-Protein Interaction via co-occurring Aligned Pattern Clusters |
| Q45943145 | Prediction of Protein-Protein Interactions. |
| Q51609595 | Prediction of RNA-binding residues in proteins from primary sequence using an enriched random forest model with a novel hybrid feature. |
| Q41860294 | Prediction of detailed enzyme functions and identification of specificity determining residues by random forests. |
| Q33387695 | Prediction of glycosylation sites using random forests |
| Q35686822 | Prediction of interactions between HIV-1 and human proteins by information integration. |
| Q38451390 | Prediction of protein-protein interaction network using a multi-objective optimization approach |
| Q33403407 | Prediction of protein-protein interaction types using association rule based classification |
| Q46418613 | Protein classification combining surface analysis and primary structure |
| Q38681085 | Protein complex analysis: From raw protein lists to protein interaction networks |
| Q33318470 | Protein function assignment through mining cross-species protein-protein interactions |
| Q34913656 | Protein inter-domain linker prediction using Random Forest and amino acid physiochemical properties |
| Q41961515 | Protein-protein interaction based on pairwise similarity. |
| Q34450771 | Protein-protein interaction predictions using text mining methods |
| Q62492646 | Protein-protein interaction sites prediction by ensemble random forests with synthetic minority oversampling technique |
| Q30002405 | Protein-protein interactions: analysis and prediction |
| Q55317399 | Quantitative estimation of soil salinity by means of different modeling methods and visible-near infrared (VIS-NIR) spectroscopy, Ebinur Lake Wetland, Northwest China. |
| Q36939329 | RVMAB: Using the Relevance Vector Machine Model Combined with Average Blocks to Predict the Interactions of Proteins from Protein Sequences |
| Q31105322 | Random Forests for Global and Regional Crop Yield Predictions |
| Q34708844 | Reconstituting protein interaction networks using parameter-dependent domain-domain interactions |
| Q37352085 | Research prioritization through prediction of future impact on biomedical science: a position paper on inference-analytics |
| Q41327061 | Rice_Phospho 1.0: a new rice-specific SVM predictor for protein phosphorylation sites |
| Q46537943 | Sequence-based prediction of protein interaction sites with an integrative method |
| Q33959387 | Simplified method to predict mutual interactions of human transcription factors based on their primary structure |
| Q30363264 | Structural bioinformatics of the interactome. |
| Q30380962 | Survey of Natural Language Processing Techniques in Bioinformatics. |
| Q41895237 | The Negatome database: a reference set of non-interacting protein pairs |
| Q31118966 | The development of a universal in silico predictor of protein-protein interactions |
| Q36120552 | The parameter sensitivity of random forests |
| Q35896436 | The use of classification trees for bioinformatics |
| Q33475174 | Triangle network motifs predict complexes by complementing high-error interactomes with structural information |
| Q37263843 | What are decision trees? |
| Q37245801 | d-Omix: a mixer of generic protein domain analysis tools |
| Q41902681 | in silico identification of protein-protein interactions in Silkworm, Bombyx mori |
| Q35102125 | ppiPre: predicting protein-protein interactions by combining heterogeneous features |
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