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,
Accurately identifying the missense mutations is of great help to alleviate the loss of protein function and structural changes, which might greatly reduce the risk of disease for tumor suppressor gen
Data repository for StructureDCA Data repository for the publication:Matsvei Tsishyn, Hugo Talibart, Marianne Rooman, Fabrizio Pucci. Structure-informed direct coupling analysis improves protein muta
Accurately identifying the missense mutations is of great help to alleviate the loss of protein function and structural changes, which might greatly reduce the risk of disease for tumor suppressor gen
Mutations (first column) were scored according to ten parameters with potential score designations in parentheses. Column headings are as follows: 1. Translation Rate; 2. Aggregation Propensity; 3. Ov
