Accuracy of a machine learning method based on structural and locational information from AlphaFold2 for predicting the pathogenicity of TARDBP and FUS gene variants in ALS.
Yuya HatanoTomohiko IshiharaOsamu OnoderaPublished in: BMC bioinformatics (2023)
MOVA is useful for predicting the virulence of rare variants in which they are concentrated at specific structural sites, and for use in combination with other prediction methods.
Keyphrases
- copy number
- machine learning
- biofilm formation
- escherichia coli
- pseudomonas aeruginosa
- genome wide
- staphylococcus aureus
- dna methylation
- antimicrobial resistance
- artificial intelligence
- amyotrophic lateral sclerosis
- health information
- big data
- gene expression
- healthcare
- transcription factor
- deep learning
- genome wide identification
- cystic fibrosis
- social media