Titlebook: Epistasis; Methods and Protocol Jason H. Moore,Scott M. Williams Book 2015 Springer Science+Business Media New York 2015 Modern genetic ana

micronutrients

V切開

Network Theory for Data-Driven Epistasis Networks,ng network centrality of genes that may reveal insights missed by individual genetic effects. We also discuss available tools to facilitate the construction and visualization of epistasis networks of GWAS data.

expository

On the Partitioning of Genetic Variance with Epistasis,alysis of data through variance partitioning, focusing on the natural and orthogonal interactions (NOIA) model. We also discuss how epistasis and epistatic variance may influence the outcome of selection, a topic that is still a matter of debate among quantitative and evolutionary geneticists.

amputation

Measuring Gene Interactions,vated measurements such as epistatic variance components has led to the misconception that epistasis is dynamically inert. Here, I review work showing that patterns of epistasis may have profound effects on evolutionary dynamics and discuss how these patterns can be measured.

表皮

Epistasis Analysis Using Artificial Intelligence, learning how to solve the problem at hand distinguishes computational evolution from other genetic programming approaches. We provide a general overview of this approach and then present a few examples of its application to real data.

慢跑

,Capacitating Epistasis—Detection and Role in the Genetic Architecture of Complex Traits,d. An overview of the theoretical foundation of the methods is presented together with a discussion on their implementation and available software for performing these analyses. We conclude by highlighting a few examples of capacitating epistasis described in the literature and its potential impacts on the genetics of complex traits.

Digitalis

Domine M. W. Leenaerts,Peter W. H. de Vreedealysis of data through variance partitioning, focusing on the natural and orthogonal interactions (NOIA) model. We also discuss how epistasis and epistatic variance may influence the outcome of selection, a topic that is still a matter of debate among quantitative and evolutionary geneticists.

瑪瑙

Sotir Ouzounov,Hans Hegt,Arthur Van Roermundvated measurements such as epistatic variance components has led to the misconception that epistasis is dynamically inert. Here, I review work showing that patterns of epistasis may have profound effects on evolutionary dynamics and discuss how these patterns can be measured.

隼鷹

Marvin Onabajo,Jose Silva-Martinez learning how to solve the problem at hand distinguishes computational evolution from other genetic programming approaches. We provide a general overview of this approach and then present a few examples of its application to real data.

reperfusion

Long-Term Selection Experiments: Epistasis and the Response to Selection,ic variation, and second, selection plateaus are frequently observed that last multiple generations before a response to selection is resumed. These features are usually attributed to the high mutation rates of quantitative traits, and the effects of linkage disequilibrium. Using previously publishe