Matches in SemOpenAlex for { <https://semopenalex.org/work/W2742538294> ?p ?o ?g. }
- W2742538294 abstract "The identification of the interactions of polymorphisms with other genetic or environmental factors for the detection of multifactorial diseases has now become both a challenge and an objective for geneticists. Unlike monogenic Mendelian diseases, the classical methods have not become too efficient for the identification of these interactions, especially with the exponential increase in the number of genetic interactions as well as the number of combinations of genotypes. Several methods have been proposed for the detection of susceptibility variants such as metaheuristics and statistical methods. Using metaheuristics, we focus on the feature selection of variables, and more precisely on the determination of the genes that increase the susceptibility to the disease, especially as these methods are more suitable for the description of complex data. Statistical methods are divided into two submethods including linkage studies and association studies. Generally these two methods are used one after the other since they are complementary. The linkage study is used initially because its objective is the localization of the chromosomal regions containing the gene(s) involved in the disease. Then, in a second step, the association study is set up to specify precisely the location of the gene. In this paper, we will present a survey of metaheuristics and statistical methods integrated in the field of human genetics and specifically multifactorial diseases in order to help genetics to find interaction between genes and environemental factor involved in those diseases." @default.
- W2742538294 created "2017-08-17" @default.
- W2742538294 creator A5023572118 @default.
- W2742538294 creator A5038041759 @default.
- W2742538294 creator A5039621617 @default.
- W2742538294 date "2017-01-01" @default.
- W2742538294 modified "2023-09-26" @default.
- W2742538294 title "Survey of Metaheuristics and Statistical Methods for Multifactorial Diseases Analyses" @default.
- W2742538294 cites W1479911746 @default.
- W2742538294 cites W1493519919 @default.
- W2742538294 cites W1499449178 @default.
- W2742538294 cites W1568834902 @default.
- W2742538294 cites W1576818901 @default.
- W2742538294 cites W1601222803 @default.
- W2742538294 cites W1637504538 @default.
- W2742538294 cites W1655097103 @default.
- W2742538294 cites W1659842140 @default.
- W2742538294 cites W1692958259 @default.
- W2742538294 cites W1976666288 @default.
- W2742538294 cites W1977104259 @default.
- W2742538294 cites W1980121234 @default.
- W2742538294 cites W1985110175 @default.
- W2742538294 cites W1987063664 @default.
- W2742538294 cites W2004288989 @default.
- W2742538294 cites W2005462790 @default.
- W2742538294 cites W2009482011 @default.
- W2742538294 cites W2020982711 @default.
- W2742538294 cites W2024060531 @default.
- W2742538294 cites W2029498633 @default.
- W2742538294 cites W2040058117 @default.
- W2742538294 cites W2041264232 @default.
- W2742538294 cites W2045310663 @default.
- W2742538294 cites W2053913299 @default.
- W2742538294 cites W2056760934 @default.
- W2742538294 cites W2066335675 @default.
- W2742538294 cites W2076526693 @default.
- W2742538294 cites W2080362750 @default.
- W2742538294 cites W2083955084 @default.
- W2742538294 cites W2084792706 @default.
- W2742538294 cites W2089890700 @default.
- W2742538294 cites W2104670598 @default.
- W2742538294 cites W2109364787 @default.
- W2742538294 cites W2109991704 @default.
- W2742538294 cites W2116045745 @default.
- W2742538294 cites W2116484405 @default.
- W2742538294 cites W2117942072 @default.
- W2742538294 cites W2134608020 @default.
- W2742538294 cites W2139135676 @default.
- W2742538294 cites W2143196848 @default.
- W2742538294 cites W2151854382 @default.
- W2742538294 cites W2158131927 @default.
- W2742538294 cites W2158698427 @default.
- W2742538294 cites W2158868693 @default.
- W2742538294 cites W2161107415 @default.
- W2742538294 cites W2164803230 @default.
- W2742538294 cites W2164855953 @default.
- W2742538294 cites W2167325069 @default.
- W2742538294 cites W2169632325 @default.
- W2742538294 cites W2171724285 @default.
- W2742538294 cites W2222796588 @default.
- W2742538294 cites W2234472791 @default.
- W2742538294 cites W226282550 @default.
- W2742538294 cites W2282962167 @default.
- W2742538294 cites W2290671409 @default.
- W2742538294 cites W2307705085 @default.
- W2742538294 cites W2330813625 @default.
- W2742538294 cites W2332142174 @default.
- W2742538294 cites W2410896593 @default.
- W2742538294 cites W2464610957 @default.
- W2742538294 cites W2473120990 @default.
- W2742538294 cites W2478675481 @default.
- W2742538294 cites W2486181131 @default.
- W2742538294 cites W2518212221 @default.
- W2742538294 cites W2546150872 @default.
- W2742538294 cites W2550157947 @default.
- W2742538294 cites W2563823863 @default.
- W2742538294 cites W2565316834 @default.
- W2742538294 cites W2566407663 @default.
- W2742538294 cites W2586298664 @default.
- W2742538294 cites W2589119740 @default.
- W2742538294 cites W2589835051 @default.
- W2742538294 cites W2591809513 @default.
- W2742538294 cites W2593468621 @default.
- W2742538294 cites W2596757303 @default.
- W2742538294 cites W2904250082 @default.
- W2742538294 cites W3023540311 @default.
- W2742538294 cites W50145612 @default.
- W2742538294 cites W852111780 @default.
- W2742538294 cites W95841981 @default.
- W2742538294 cites W96717503 @default.
- W2742538294 doi "https://doi.org/10.3934/medsci.2017.3.291" @default.
- W2742538294 hasPublicationYear "2017" @default.
- W2742538294 type Work @default.
- W2742538294 sameAs 2742538294 @default.
- W2742538294 citedByCount "3" @default.
- W2742538294 countsByYear W27425382942018 @default.
- W2742538294 countsByYear W27425382942019 @default.
- W2742538294 crossrefType "journal-article" @default.
- W2742538294 hasAuthorship W2742538294A5023572118 @default.
- W2742538294 hasAuthorship W2742538294A5038041759 @default.