PhosHSGN: Deep Neural Networks Combining Sequence and Protein Spatial Information to Improve Protein Phosphorylation Site Prediction.
Jiale LuHaibin ChenJi QiuPublished in: IEEE Access (2024)
Keyphrases
- spatial information
- amino acids
- protein sequences
- tertiary structure
- secondary structure
- protein tertiary structure
- subcellular localization
- protein structure
- neural network
- protein secondary structure
- protein structure prediction
- contact map
- amino acid sequences
- sequence alignment
- contact maps
- sequence analysis
- protein secondary structure prediction
- psi blast
- protein function
- multiple sequence alignments
- spatial distribution
- protein interaction
- remote homology detection
- spatial relations
- temporal information
- drug design
- multiple sequence alignment
- experimentally determined
- spatial resolution
- sequence databases
- physicochemical properties
- spatial relationships
- local binary pattern
- protein classification
- protein families
- protein protein interactions
- genomic sequences
- intensity values
- rna secondary structures
- color histogram
- genome sequences
- prediction accuracy
- artificial neural networks
- spatial context
- visual words
- closely related
- protein structural