Ontology highlight
ABSTRACT:
SUBMITTER: Abakarova M
PROVIDER: S-EPMC10653582 | biostudies-literature | 2023 Nov
REPOSITORIES: biostudies-literature
Abakarova Marina M Marquet Céline C Rera Michael M Rost Burkhard B Laine Elodie E
Genome biology and evolution 20231101 11
The wealth of genomic data has boosted the development of computational methods predicting the phenotypic outcomes of missense variants. The most accurate ones exploit multiple sequence alignments, which can be costly to generate. Recent efforts for democratizing protein structure prediction have overcome this bottleneck by leveraging the fast homology search of MMseqs2. Here, we show the usefulness of this strategy for mutational outcome prediction through a large-scale assessment of 1.5M misse ...[more]