Snapshots from the MutaGene server show the results of analysis of EGFR gene with a Pan-cancer model. (A) Scatterplot with expected mutability versus observed mutational frequencies. (B) Top list of mutations ranked by their B-Scores. (C) EGFR nucleotide and translated protein sequence shows per-nucleotide site mutability per codon mutability as well as mutabilities of nucleotide and codon substitutions (heatmaps). Mutations observed in tumors from ICGC repository are shown as circles colored by their prediction status: Driver, Potential driver, and Passenger. Missense mutation p.Arg252Pro is shown with a blue arrow.</p
Cancer drivers are genomic alterations that provide cells containing them with a selective advantage...
Identifying molecular cancer drivers is critical for precision oncology. Multiple advanced algorithm...
The catalogue of tumour-specific somatic mutations (SMs) is growing rapidly owing to the advent of n...
Identifying driver mutations in cancer is notoriously difficult. To date, recurrence of a mutation i...
Identifying driver mutations in cancer is notoriously difficult. To date, recurrence of a mutation i...
Abstract Background Because driver mutations provide selective advantage to the mutant clone, they t...
<p>Each row represents a mutated gene and each column represents an individual tumor. Shown in green...
Mutability of all theoretically possible codon substitutions (“not observed”) and all substitutions ...
nucleotide and codon tables used for plots and figures and analysis, have all mutations in 520 cance...
A) The circle graph represents for each case (n = 74) the proportion of driver mutations detected in...
<p>Percentages are the proportion of tumors having a mutation within a subtype, e.g. 37% of Bronchio...
<p>Coding mutations in known cancer genes (A) and candidate genes (B) are indicated with different c...
<div><p>Cancer is a genetic disease that develops through a series of somatic mutations, a subset of...
MotivationMost approaches used to identify cancer driver genes focus, true to their name, on entire ...
<p>Mutation plots showing the amount of genes that need to be sequenced (y-axis) in order to find a ...
Cancer drivers are genomic alterations that provide cells containing them with a selective advantage...
Identifying molecular cancer drivers is critical for precision oncology. Multiple advanced algorithm...
The catalogue of tumour-specific somatic mutations (SMs) is growing rapidly owing to the advent of n...
Identifying driver mutations in cancer is notoriously difficult. To date, recurrence of a mutation i...
Identifying driver mutations in cancer is notoriously difficult. To date, recurrence of a mutation i...
Abstract Background Because driver mutations provide selective advantage to the mutant clone, they t...
<p>Each row represents a mutated gene and each column represents an individual tumor. Shown in green...
Mutability of all theoretically possible codon substitutions (“not observed”) and all substitutions ...
nucleotide and codon tables used for plots and figures and analysis, have all mutations in 520 cance...
A) The circle graph represents for each case (n = 74) the proportion of driver mutations detected in...
<p>Percentages are the proportion of tumors having a mutation within a subtype, e.g. 37% of Bronchio...
<p>Coding mutations in known cancer genes (A) and candidate genes (B) are indicated with different c...
<div><p>Cancer is a genetic disease that develops through a series of somatic mutations, a subset of...
MotivationMost approaches used to identify cancer driver genes focus, true to their name, on entire ...
<p>Mutation plots showing the amount of genes that need to be sequenced (y-axis) in order to find a ...
Cancer drivers are genomic alterations that provide cells containing them with a selective advantage...
Identifying molecular cancer drivers is critical for precision oncology. Multiple advanced algorithm...
The catalogue of tumour-specific somatic mutations (SMs) is growing rapidly owing to the advent of n...