نتایج جستجو برای: g x e interaction
تعداد نتایج: 2398407 فیلتر نتایج به سال:
the objective of this study was to compare non-parametric stability procedures, and to apply different non-parametric tests for genotype × environment interaction (g×e) on seed yield data of 17 chickpea genotypes grown during 2004-05 growing seasons in 10 rainfed environments in iran. the non-parametric measures used for g × e interaction were highly significant (p
let $g$ be a simple graph of order $n$ and size $m$.the edge covering of $g$ is a set of edges such that every vertex of $g$ is incident to at least one edge of the set. the edge cover polynomial of $g$ is the polynomial$e(g,x)=sum_{i=rho(g)}^{m} e(g,i) x^{i}$,where $e(g,i)$ is the number of edge coverings of $g$ of size $i$, and$rho(g)$ is the edge covering number of $g$. in this paper we stud...
Genome-wide association studies of gene-environment interaction (GxE GWAS) are becoming popular. As with main effects GWAS, quantile-quantile plots (QQ-plots) and Genomic Control are being used to assess and correct for population substructure. However, in G x E work these approaches can be seriously misleading, as we illustrate; QQ-plots may give strong indications of substructure when absolut...
Let $G$ be a simple graph of order $n$ and size $m$.The edge covering of $G$ is a set of edges such that every vertex of $G$ is incident to at least one edge of the set. The edge cover polynomial of $G$ is the polynomial$E(G,x)=sum_{i=rho(G)}^{m} e(G,i) x^{i}$,where $e(G,i)$ is the number of edge coverings of $G$ of size $i$, and$rho(G)$ is the edge covering number of $G$. In this paper we stud...
In order to study effect of G×E interaction on yield of genotypes in three environment. These genotypes were planted using RCB design with 3 replications in Esfahan, Kermanshah and Varamin. The results of combined analysis of variance for yield showed significant difference for genotype, location and G×E interaction effects. Because of significant G×E interaction stability analysis methods AMMI...
Gene x environment (G x E) interactions mediating depressive symptoms have been separately identified in the stress-sensitive serotonergic (5-HTTLPR) and corticotropin-releasing hormone (CRHR1) systems. Our objective was to examine whether the effects of child abuse are moderated by gene x gene (G x G) interactions between CRHR1 and 5-HTTLPR polymorphisms. We used an association study examining...
a graph g = (v,e) with p vertices and q edges is said to be a total mean cordial graph if there exists a function f : v (g) → {0, 1, 2} such that f(xy) = [(f(x)+f(y))/2] where x, y ∈ v (g), xy ∈ e(g), and the total number of 0, 1 and 2 are balanced. that is |evf (i) − evf (j)| ≤ 1, i, j ∈ {0, 1, 2} where evf (x) denotes the total number of vertices and edges labeled with x (x = 0, 1, 2). in thi...
Identifying gene-environment (G x E) interactions has become a crucial issue in the past decades. Different methods have been proposed to test for G x E interactions in the framework of linkage or association testing. However, their respective performances have rarely been compared. Using Genetic Analysis Workshop 15 simulated data, we compared the power of four methods: one based on affected s...
In the study of complex diseases, it may be important to test hypotheses related to gene-gene (G x G) interaction. The success of such studies depends critically on obtaining adequate sample sizes. In this paper, the author investigates sample size requirements for studies of G x G interaction, focusing on four study designs: the matched-case-control design, the case-sibling design, the case-pa...
Let $kgeq 1$ be an integer, and $G=(V,E)$ be a finite and simplegraph. The closed neighborhood $N_G[e]$ of an edge $e$ in a graph$G$ is the set consisting of $e$ and all edges having a commonend-vertex with $e$. A signed Roman edge $k$-dominating function(SREkDF) on a graph $G$ is a function $f:E rightarrow{-1,1,2}$ satisfying the conditions that (i) for every edge $e$of $G$, $sum _{xin N[e]} f...
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