Interpretable feature extraction and dimensionality reduction in ESM2 for protein localization prediction.
Zeyu LuoRui WangYawen SunJunhao LiuHerman Z. Q. ChenYu-Juan ZhangPublished in: Briefings Bioinform. (2024)
Keyphrases
- feature extraction
- dimensionality reduction
- subcellular localization
- principal component analysis
- contact map
- protein secondary structure
- linear discriminant analysis
- protein structure prediction
- pattern recognition
- contact maps
- feature selection
- high dimensional data
- low dimensional
- feature space
- drug design
- protein structure
- protein secondary structure prediction
- manifold learning
- principal components
- protein tertiary structure
- prediction accuracy
- wavelet transform
- feature vectors
- high dimensional
- dimension reduction
- experimentally determined
- discriminant projection
- data representation
- discriminant analysis
- high dimensionality
- preprocessing
- face recognition
- prediction model
- protein function prediction
- protein sequences
- image processing
- predicting protein
- data points
- gene prediction
- protein function
- structure preserving
- dimensionality reduction methods
- protein protein interactions
- feature representation
- feature set
- pattern classification
- graph embedding
- protein interaction
- drug discovery
- pattern recognition and machine learning
- multiple sequence alignments
- extracted features
- support vector machine svm
- neural network