Remarks on the evolutionary effect of natural selection.
نویسنده
چکیده
The so-called "Fundamental Theorem of Natural Selectiion", than the mean fitness of a population increases with time under natural selection, is known not to be true, as a mathematical theorem, when fitnesses depend on more than one locus. Although this observation may not have particular biological relevance, (so that mean fitness may well increase in the great majority of interesting situations), it does suggest that it is of interest to find an evolutionary result which is correct as a mathematical theorem, no matter how many loci are involved. The aim of the present note is to prove an evolutionary theorem relating to the variance in fitness, rather that the mean: this theorem is true for an arbitrary number of loci, as well as for arbitrary (fixed) fitness parameters and arbitrary linkage between loci. Connections are briefly discussed between this theorem and the principle of quasi-linkage equilibrium.
منابع مشابه
Improving of Feature Selection in Speech Emotion Recognition Based-on Hybrid Evolutionary Algorithms
One of the important issues in speech emotion recognizing is selecting of appropriate feature sets in order to improve the detection rate and classification accuracy. In last studies researchers tried to select the appropriate features for classification by using the selecting and reducing the space of features methods, such as the Fisher and PCA. In this research, a hybrid evolutionary algorit...
متن کاملSelection of energy source and evolutionary stable strategies for power plants under financial intervention of government
Currently, many socially responsible governments adopt economic incentives and deterrents to manage environmental impacts of electricity suppliers. Considering the Stackelberg leadership of the government, the government’s role in the competition of power plants in an electricity market is investigated. A one-population evolutionary game model of power plants is developed to study how their pro...
متن کاملNovel Radial Basis Function Neural Networks based on Probabilistic Evolutionary and Gaussian Mixture Model for Satellites Optimum Selection
In this study, two novel learning algorithms have been applied on Radial Basis Function Neural Network (RBFNN) to approximate the functions with high non-linear order. The Probabilistic Evolutionary (PE) and Gaussian Mixture Model (GMM) techniques are proposed to significantly minimize the error functions. The main idea is concerning the various strategies to optimize the procedure of Gradient ...
متن کاملGreen Space Suitability Analysis Using Evolutionary Algorithm and Weighted Linear Combination (WLC) Method
With current new urban developments, no balance can be found between green spaces and open areas present within urban networks and natural land patterns since urban networks are dominating ecological networks. Accordingly, one of the major tasks of urban and regional planners is the optimal land use allocation to urban green spaces. Therefore, to achieve this goal in this research, locations of...
متن کاملA Note on Evolutionary Rate Estimation in Bayesian Evolutionary Analysis: Focus on Pathogens
Bayesian evolutionary analysis provide a statistically sound and flexible framework for estimation of evolutionary parameters. In this method, posterior estimates of evolutionary rate (μ) are derived by combining evolutionary information in the data with researcher’s prior knowledge about the true value of μ. Nucleotide sequence samples of fast evolving pathogens that are taken at d...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Genetics
دوره 83 3 PT.2 شماره
صفحات -
تاریخ انتشار 1976