TY - DATA AB - Data on pollinator visitation to wild snapdragons in a natural hybrid zone, collected as part of Tom Ellis' PhD thesis (submitted February 2016). Snapdragon flowers have a mouth-like structure which pollinators must open to access nectar. We placed 5mm cellophane tags in these mouths, which are held in place by the pressure of the flower until a pollinator visits. When she opens the flower, the tag drops out, and one can infer a visit. We surveyed plants over multiple days in 2010, 2011 and 2012. Also included are data on phenotypic and demographic variables which may be explanatory variables for pollinator visitation. AU - Ellis, Thomas ID - 5552 TI - Pollinator visitation data for wild Antirrhinum majus plants, with phenotypic and frequency data. ER - TY - DATA AB - The data stored here is used in Murat Tugrul's PhD thesis (Chapter 3), which is related to the evolution of bacterial RNA polymerase binding. Magdalena Steinrueck (PhD Student in Calin Guet's group at IST Austria) performed the experiments and created the data on de novo promoter evolution. Fabienne Jesse (PhD Student in Jon Bollback's group at IST Austria) performed the experiments and created the data on lac promoter evolution. AU - Tugrul, Murat ID - 5554 KW - RNAP binding KW - de novo promoter evolution KW - lac promoter TI - Experimental Data for Binding Site Evolution of Bacterial RNA Polymerase ER - TY - CONF AB - Evolutionary algorithms (EAs) form a popular optimisation paradigm inspired by natural evolution. In recent years the field of evolutionary computation has developed a rigorous analytical theory to analyse their runtime on many illustrative problems. Here we apply this theory to a simple model of natural evolution. In the Strong Selection Weak Mutation (SSWM) evolutionary regime the time between occurrence of new mutations is much longer than the time it takes for a new beneficial mutation to take over the population. In this situation, the population only contains copies of one genotype and evolution can be modelled as a (1+1)-type process where the probability of accepting a new genotype (improvements or worsenings) depends on the change in fitness. We present an initial runtime analysis of SSWM, quantifying its performance for various parameters and investigating differences to the (1+1) EA. We show that SSWM can have a moderate advantage over the (1+1) EA at crossing fitness valleys and study an example where SSWM outperforms the (1+1) EA by taking advantage of information on the fitness gradient. AU - Paixao, Tiago AU - Sudholt, Dirk AU - Heredia, Jorge AU - Trubenova, Barbora ID - 1430 T2 - Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation TI - First steps towards a runtime comparison of natural and artificial evolution ER - TY - JOUR AB - Evolutionary biologists have an array of powerful theoretical techniques that can accurately predict changes in the genetic composition of populations. Changes in gene frequencies and genetic associations between loci can be tracked as they respond to a wide variety of evolutionary forces. However, it is often less clear how to decompose these various forces into components that accurately reflect the underlying biology. Here, we present several issues that arise in the definition and interpretation of selection and selection coefficients, focusing on insights gained through the examination of selection coefficients in multilocus notation. Using this notation, we discuss how its flexibility-which allows different biological units to be identified as targets of selection-is reflected in the interpretation of the coefficients that the notation generates. In many situations, it can be difficult to agree on whether loci can be considered to be under "direct" versus "indirect" selection, or to quantify this selection. We present arguments for what the terms direct and indirect selection might best encompass, considering a range of issues, from viability and sexual selection to kin selection. We show how multilocus notation can discriminate between direct and indirect selection, and describe when it can do so. AU - Barton, Nicholas H AU - Servedio, Maria ID - 1519 IS - 5 JF - Evolution TI - The interpretation of selection coefficients VL - 69 ER - TY - JOUR AB - The theory of population genetics and evolutionary computation have been evolving separately for nearly 30 years. Many results have been independently obtained in both fields and many others are unique to its respective field. We aim to bridge this gap by developing a unifying framework for evolutionary processes that allows both evolutionary algorithms and population genetics models to be cast in the same formal framework. The framework we present here decomposes the evolutionary process into its several components in order to facilitate the identification of similarities between different models. In particular, we propose a classification of evolutionary operators based on the defining properties of the different components. We cast several commonly used operators from both fields into this common framework. Using this, we map different evolutionary and genetic algorithms to different evolutionary regimes and identify candidates with the most potential for the translation of results between the fields. This provides a unified description of evolutionary processes and represents a stepping stone towards new tools and results to both fields. AU - Paixao, Tiago AU - Badkobeh, Golnaz AU - Barton, Nicholas H AU - Çörüş, Doğan AU - Dang, Duccuong AU - Friedrich, Tobias AU - Lehre, Per AU - Sudholt, Dirk AU - Sutton, Andrew AU - Trubenova, Barbora ID - 1542 JF - Journal of Theoretical Biology TI - Toward a unifying framework for evolutionary processes VL - 383 ER -