Predicting COVID-19 disease severity from SARS-CoV-2 spike protein sequence by mixed effects machine learning.
Bahrad A. SokhansanjGail L. RosenPublished in: Comput. Biol. Medicine (2022)
Keyphrases
- protein sequences
- mixed effects
- computational biology
- machine learning
- severe acute respiratory syndrome
- random effects
- protein secondary structure
- secondary structure
- protein classification
- protein structure
- protein secondary structure prediction
- amino acids
- public health
- sequence analysis
- predicting protein
- structural motifs
- protein structure prediction
- machine learning methods
- molecular biology
- feature selection
- computational approaches
- protein function
- protein folding
- machine learning algorithms
- information extraction
- amino acid composition
- data mining
- amino acid sequences
- decision trees
- protein structural
- hidden markov models
- experimentally determined
- remote homology detection