To the best of our knowledge, this is the first study showing deviations from HWE and selection involving a modifier gene involved in a Mendelian disorder.
There is a rich body of theory and empirical work on the evolution of selfing in flowering plants [e.g. [ 1, 2, 4- 7, 9, 10]], but practically none of it involves an explicit role of selection involving time-limitation.
For each random sample, the number of genes that overlapped a region with signatures of selection involving the populations was recorded, and this was repeated for 1,000 trials.
A common approach to gene selection involves selecting a handful of top-ranking genes that best differentiate sample classes (such as tumor vs. normal tissue) or are most predictive of clinical outcome.
For explicit assumptions that being a unit of selection involves having an adaptation at that level, see Brandon 1982, 1985; Burian 1983; Mitchell 1987; Maynard Smith 1976; Vrba 1984.
Previous studies (e.g. Bozic et al. 2010; Zhuang et al. 2011) have suggested that processes of competition and selection involve a bilateral frontal system, although the involvement of RIFG may be weaker than that of the LIFG.
In contrast, "K selection" involves a scenario in which stable conditions result in an environment in which resources may often be insufficient to support maximal growth, thus favoring reduced mortality rates and improved competitive abilities.
The task of algorithm selection involves choosing an algorithm from a set of algorithms on a per-instance basis in order to exploit the varying performance of algorithms over a set of instances.
If color selection involves a spouse, be prepared to compromise.
Given a data set, model selection involves finding the statistical model that best captures the properties and regularities present in the data.
