DeepDISOBind: accurate prediction of RNA-, DNA- and protein-binding intrinsically disordered residues with deep multi-task learning.
Fuhao ZhangBi ZhaoWenbo ShiMin LiLukasz A. KurganPublished in: Briefings Bioinform. (2022)
Keyphrases
- multi task learning
- experimentally determined
- intrinsically disordered
- secondary structure
- protein sequences
- rna sequences
- amino acids
- disordered regions
- amino acid sequences
- protein structure
- sequence analysis
- genome sequences
- contact map
- multi task
- predicting protein
- protein structure prediction
- protein function
- gaussian processes
- computational biology
- learning tasks
- protein protein
- biological sequences
- dna binding
- binding sites
- cis regulatory
- learning problems
- molecular biology
- protein folding
- high order
- protein interaction
- protein protein interactions
- transfer learning
- multiple sequence alignments
- learning algorithm
- genome wide
- computational methods
- learning models
- theoretical analysis
- multi class
- transcription factor binding sites
- coarse grained
- gaussian process
- genomic sequences
- motif discovery
- sequence alignment
- dna sequences
- high throughput