{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T20:35:00Z","timestamp":1772138100398,"version":"3.50.1"},"reference-count":13,"publisher":"Oxford University Press (OUP)","issue":"6","license":[{"start":{"date-parts":[[2019,11,19]],"date-time":"2019-11-19T00:00:00Z","timestamp":1574121600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/100010663","name":"European Research Council","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100010663","id-type":"DOI","asserted-by":"publisher"}]},{"name":"European Union\u2019s Seventh Framework Programme","award":["FP7\/2007-2013"],"award-info":[{"award-number":["FP7\/2007-2013"]}]},{"name":"European Union\u2019s Seventh Framework Programme","award":["335980_EinME"],"award-info":[{"award-number":["335980_EinME"]}]},{"name":"Zimin Foundation"},{"name":"Woman Scientists"},{"DOI":"10.13039\/100017169","name":"Centre for Genomic Regulation","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100017169","id-type":"DOI","asserted-by":"crossref"}]},{"name":"CRG"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,3,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>Epistasis, the context-dependence of the contribution of an amino acid substitution to fitness, is common in evolution. To detect epistasis, fitness must be measured for at least four genotypes: the reference genotype, two different single mutants and a double mutant with both of the single mutations. For higher-order epistasis of the order n, fitness has to be measured for all 2n genotypes of an n-dimensional hypercube in genotype space forming a \u2018combinatorially complete dataset\u2019. So far, only a handful of such datasets have been produced by manual curation. Concurrently, random mutagenesis experiments have produced measurements of fitness and other phenotypes in a high-throughput manner, potentially containing a number of combinatorially complete datasets.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>We present an effective recursive algorithm for finding all hypercube structures in random mutagenesis experimental data. To test the algorithm, we applied it to the data from a recent HIS3 protein dataset and found all 199\u00a0847\u00a0053 unique combinatorially complete genotype combinations of dimensionality ranging from 2 to 12. The algorithm may be useful for researchers looking for higher-order epistasis in their high-throughput experimental data.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>https:\/\/github.com\/ivankovlab\/HypercubeME.git.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Supplementary information<\/jats:title>\n                    <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btz841","type":"journal-article","created":{"date-parts":[[2019,11,18]],"date-time":"2019-11-18T15:10:32Z","timestamp":1574089832000},"page":"1960-1962","source":"Crossref","is-referenced-by-count":7,"title":["HypercubeME: two hundred million combinatorially complete datasets from a single experiment"],"prefix":"10.1093","volume":"36","author":[{"given":"Laura\u00a0A","family":"Esteban","sequence":"first","affiliation":[{"name":"Universitat Pompeu Fabra (UPF) , Barcelona 08003, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lyubov R","family":"Lonishin","sequence":"additional","affiliation":[{"name":"Faculty of Medical Physics, Institute of Biomedical System and Technologies, Peter the Great Saint Petersburg Polytechnic University , Saint Petersburg 195251, Russia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daniil M","family":"Bobrovskiy","sequence":"additional","affiliation":[{"name":"Faculty of Bioengineering and Bioinformatics, Moscow State University , Moscow 119234, Russia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gregory","family":"Leleytner","sequence":"additional","affiliation":[{"name":"Department of Innovation and High Technology, Moscow Institute of Physics and Technology , Moscow 141701, Russia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Natalya S","family":"Bogatyreva","sequence":"additional","affiliation":[{"name":"Universitat Pompeu Fabra (UPF) , Barcelona 08003, Spain"},{"name":"Bioinformatics and Genomics Programme, Center for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology , 08003 Barcelona, Spain"},{"name":"Laboratory of Protein Physics, Institute of Protein Research of the Russian Academy of Sciences , Moscow 142290, Russia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fyodor A","family":"Kondrashov","sequence":"additional","affiliation":[{"name":"Institute of Science and Technology Austria , 3400 Klosterneuburg, Austria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8224-4118","authenticated-orcid":false,"given":"Dmitry N","family":"Ivankov","sequence":"additional","affiliation":[{"name":"Center of Life Sciences, Skolkovo Institute of Science and Technology , Moscow 121205, Russia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2019,11,19]]},"reference":[{"key":"2023060912014084000_btz841-B1","first-page":"648","article-title":"Inference of high-order epistatic interactions using generalized relevance learning vector quantization with parametric adjustment","author":"de Araujo","year":"2016","journal-title":"IEEE International Conference in Tools with Artificial Intelligence (ICTAI)"},{"key":"2023060912014084000_btz841-B2","doi-asserted-by":"crossref","first-page":"535","DOI":"10.1038\/nature11510","article-title":"Epistasis as the primary factor in molecular evolution","volume":"490","author":"Breen","year":"2012","journal-title":"Nature"},{"key":"2023060912014084000_btz841-B3","doi-asserted-by":"crossref","first-page":"837","DOI":"10.1126\/science.aae0568","article-title":"The fitness landscape of a tRNA gene","volume":"352","author":"Li","year":"2016","journal-title":"Science"},{"key":"2023060912014084000_btz841-B4","first-page":"E7550","article-title":"Inferring the shape of global epistasis","volume":"118","author":"Otwinowski","year":"2018","journal-title":"Proc. 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