Loading...
Please wait, while we are loading the content...
Similar Documents
Interpretable Knowledge Acquisition for Predicting Bioluminescent Proteins Using an Evolutionary Fuzzy Classifier Method
| Content Provider | CiteSeerX |
|---|---|
| Author | Huang, Hui-Ling Lee, Hua-Chin Charoenkwan, Phasit Huang, Wen-Lin Shu, Li-Sun Ho, Shinn-Ying |
| Abstract | Abstract—New applications of using bioluminescent proteins (BLPs) are constantly increasing in a variety of research fields such as protein engineering of using single-cell bioluminescent organisms to determine how animals move through water. In this study, we propose a knowledge acquisition method for characterizing BLPs and understanding their functions using a compact set of fuzzy rules. The rule set was obtained by designing an if-then fuzzy-rule-based bioluminescent protein classifier (named iFBPC) with physicochemical properties as input features. In designing iFBPC, feature selection, membership function design, and fuzzy rule base generation are all simultaneously optimized using an intelligent genetic algorithm (IGA). We used the same benchmark dataset for comparisons used in existing SVM-based prediction methods BLProt and PBLP using 100 and 15 features of physicochemical properties, respectively. The classifier iFBPC has two fuzzy rules (one for BLP and the other for non-BLP) and four physicochemical properties with test accuracy of 74.82 % where BLProt and PBLP have accuracies of 80.06% and 81.79%, respectively. The four physicochemical properties are structures, protein linkers, nucleation, and membrane proteins in the AAindex database. The analysis of characterizing BLPs was conducted based on knowledge of the fuzzy rule base. Keywords-bioluminescent proteins; feature selection; fuzzy rules; genetic algorithm; knowledge acquisition; physicochemical properties. I. |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Physicochemical Property Predicting Bioluminescent Protein Fuzzy Rule Interpretable Knowledge Acquisition Evolutionary Fuzzy Classifier Method Feature Selection Fuzzy Rule Base Generation Research Field Membrane Protein Test Accuracy Keywords-bioluminescent Protein Benchmark Dataset Protein Linkers Intelligent Genetic Algorithm Svm-based Prediction Method Blprot Bioluminescent Protein Knowledge Acquisition Method Protein Engineering Genetic Algorithm Abstract New Application Classifier Ifbpc Single-cell Bioluminescent Organism Input Feature Membership Function Design Aaindex Database Rule Set Fuzzy Rule Base If-then Fuzzy-rule-based Bioluminescent Protein Classifier Compact Set |
| Content Type | Text |
