Gene

Biology

Somatic cell

Selection (genetic algorithm)

Computer science

Computational biology

Evolutionary biology

Genetics

Genome

Haploinsufficiency

Artificial intelligence

Negative selection

Cancer

Phenotype

Cell

(Cell 171, 1029–1041.e1–e15; November 16, 2017) It has come to our attention that in the Results and Discussion of the above article, we neglected to cite Davoli et al., 2013Davoli T. Xu A.W. Mengwasser K.E. Sack L.M. Yoon J.C. Park P.J. Elledge S.J. Cumulative haploinsufficiency and triplosensitivity drive aneuploidy patterns and shape the cancer genome.Cell. 2013; 155: 948-962Abstract Full Text Full Text PDF PubMed Scopus (476) Google Scholar. This paper identified several of the cancer driver genes we mentioned in our paper and provided estimates of the number of genes under positive selection in cancer. The text and references in the online version of our paper have been corrected accordingly. We apologize for the omission and any inconvenience it may have caused to the scientific community. Universal Patterns of Selection in Cancer and Somatic TissuesMartincorena et al.CellOctober 19, 2017In BriefAdapting an evolutionary genomics approach to cancer highlights a limited impact of negative selection on cancer genomes and significant variations in the proportion of coding driver mutations per tumor among different tumor types. Full-Text PDF Open Access

Universal Patterns of Selection in Cancer and Somatic Tissues