Predicting the functional impact of protein mutations: application to cancer genomics
Memorial Sloan Kettering Cancer Center
Abstract
As large-scale re-sequencing of genomes reveals many protein mutations, especially in human cancer tissues, prediction of their likely functional impact becomes important practical goal. Here, we introduce a new functional impact score (FIS) for amino acid residue changes using evolutionary conservation patterns. The information in these patterns is derived from aligned families and sub-families of sequence homologs within and between species using combinatorial entropy formalism. The score performs well on a large set of human protein mutations in separating disease-associated variants (∼19 200), assumed to be strongly functional, from common polymorphisms (∼35 600), assumed to be weakly functional (area…
Citation impact
- FWCI
- 30.99
- Percentile
- 100%
- References
- 64
Authors
3Topics & keywords
- Biology
- Computational biology
- Genetics
- Genome
- Functional genomics
- Cancer
- Gene
- Genomics
- Life in Land