Relevant bibliographies by topics / Adaptive or fitness landscapes

Academic literature on the topic 'Adaptive or fitness landscapes'

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Published: 9 March 2023
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Journal articles on the topic "Adaptive or fitness landscapes"

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Zheng, Liming, and Shiqi Luo. "Adaptive Differential Evolution Algorithm Based on Fitness Landscape Characteristic." Mathematics 10, no. 9 (May 1, 2022): 1511. http://dx.doi.org/10.3390/math10091511.

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Differential evolution (DE) is a simple, effective, and robust algorithm, which has demonstrated excellent performance in dealing with global optimization problems. However, different search strategies are designed for different fitness landscape conditions to find the optimal solution, and there is not a single strategy that can be suitable for all fitness landscapes. As a result, developing a strategy to adaptively steer population evolution based on fitness landscape is critical. Motivated by this fact, in this paper, a novel adaptive DE based on fitness landscape (FL-ADE) is proposed, which utilizes the local fitness landscape characteristics in each generation population to (1) adjust the population size adaptively; (2) generate DE/current-to-pcbest mutation strategy. The adaptive mechanism is based on local fitness landscape characteristics of the population and enables to decrease or increase the population size during the search. Due to the adaptive adjustment of population size for different fitness landscapes and evolutionary processes, computational resources can be rationally assigned at different evolutionary stages to satisfy diverse requirements of different fitness landscapes. Besides, the DE/current-to-pcbest mutation strategy, which randomly chooses one of the top p% individuals from the archive cbest of local optimal individuals to be the pcbest, is also an adaptive strategy based on fitness landscape characteristic. Using the individuals that are approximated as local optimums increases the algorithm’s ability to explore complex multimodal functions and avoids stagnation due to the use of individuals with good fitness values. Experiments are conducted on CEC2014 benchmark test suit to demonstrate the performance of the proposed FL-ADE algorithm, and the results show that the proposed FL-ADE algorithm performs better than the other seven highly performing state-of-art DE variants, even the winner of the CEC2014 and CEC2017. In addition, the effectiveness of the adaptive population mechanism and DE/current-to-pcbest mutation strategy based on landscape fitness proposed in this paper are respectively verified.
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Srivastava, Malvika, and Joshua L. Payne. "On the incongruence of genotype-phenotype and fitness landscapes." PLOS Computational Biology 18, no. 9 (September 19, 2022): e1010524. http://dx.doi.org/10.1371/journal.pcbi.1010524.

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The mapping from genotype to phenotype to fitness typically involves multiple nonlinearities that can transform the effects of mutations. For example, mutations may contribute additively to a phenotype, but their effects on fitness may combine non-additively because selection favors a low or intermediate value of that phenotype. This can cause incongruence between the topographical properties of a fitness landscape and its underlying genotype-phenotype landscape. Yet, genotype-phenotype landscapes are often used as a proxy for fitness landscapes to study the dynamics and predictability of evolution. Here, we use theoretical models and empirical data on transcription factor-DNA interactions to systematically study the incongruence of genotype-phenotype and fitness landscapes when selection favors a low or intermediate phenotypic value. Using the theoretical models, we prove a number of fundamental results. For example, selection for low or intermediate phenotypic values does not change simple sign epistasis into reciprocal sign epistasis, implying that genotype-phenotype landscapes with only simple sign epistasis motifs will always give rise to single-peaked fitness landscapes under such selection. More broadly, we show that such selection tends to create fitness landscapes that are more rugged than the underlying genotype-phenotype landscape, but this increased ruggedness typically does not frustrate adaptive evolution because the local adaptive peaks in the fitness landscape tend to be nearly as tall as the global peak. Many of these results carry forward to the empirical genotype-phenotype landscapes, which may help to explain why low- and intermediate-affinity transcription factor-DNA interactions are so prevalent in eukaryotic gene regulation.
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Cervera, Héctor, Jasna Lalić, and Santiago F. Elena. "Effect of Host Species on Topography of the Fitness Landscape for a Plant RNA Virus." Journal of Virology 90, no. 22 (August 31, 2016): 10160–69. http://dx.doi.org/10.1128/jvi.01243-16.

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ABSTRACTAdaptive fitness landscapes are a fundamental concept in evolutionary biology that relate the genotypes of individuals to their fitness. In the end, the evolutionary fate of evolving populations depends on the topography of the landscape, that is, the numbers of accessible mutational pathways and possible fitness peaks (i.e., adaptive solutions). For a long time, fitness landscapes were only theoretical constructions due to a lack of precise information on the mapping between genotypes and phenotypes. In recent years, however, efforts have been devoted to characterizing the properties of empirical fitness landscapes for individual proteins or for microbes adapting to artificial environments. In a previous study, we characterized the properties of the empirical fitness landscape defined by the first five mutations fixed during adaptation of tobacco etch potyvirus (TEV) to a new experimental host,Arabidopsis thaliana. Here we evaluate the topography of this landscape in the ancestral hostNicotiana tabacum. By comparing the topographies of the landscapes for the two hosts, we found that some features remained similar, such as the existence of fitness holes and the prevalence of epistasis, including cases of sign and reciprocal sign epistasis that created rugged, uncorrelated, and highly random topographies. However, we also observed significant differences in the fine-grained details between the two landscapes due to changes in the fitness and epistatic interactions of some genotypes. Our results support the idea that not only fitness tradeoffs between hosts but also topographical incongruences among fitness landscapes in alternative hosts may contribute to virus specialization.IMPORTANCEDespite its importance for understanding virus evolutionary dynamics, very little is known about the topography of virus adaptive fitness landscapes, and even less is known about the effects that different host species and environmental conditions may have on this topography. To bridge this gap, we evaluated the topography of a small fitness landscape formed by all genotypes that result from every possible combination of the first five mutations fixed during adaptation of TEV to the novel hostA. thaliana. To assess the effect that host species may have on this topography, we evaluated the fitness of every genotype in both the ancestral and novel hosts. We found that both landscapes share some macroscopic properties, such as the existence of holes and being highly rugged and uncorrelated, yet they differ in microscopic details due to changes in the magnitude and sign of fitness and epistatic effects.
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Li, Ye, and Claus O. Wilke. "Digital Evolution in Time-Dependent Fitness Landscapes." Artificial Life 10, no. 2 (March 2004): 123–34. http://dx.doi.org/10.1162/106454604773563559.

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We study the response of populations of digital organisms that adapt to a time-varying (periodic) fitness landscape of two oscillating peaks. We corroborate in general predictions from quasi-species theory in dynamic landscapes, such as adaptation to the average fitness landscape at small periods (high frequency) and quasistatic adaptation at large periods (low frequency). We also observe adaptive phase shifts (time lags between a change in the fitness landscape and an adaptive change in the population) that indicate a low-pass filter effect, in agreement with existing theory. Finally, we witness long-term adaptation to fluctuating environments not anticipated in previous theoretical work.
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Trujillo, Leonardo, Paul Banse, and Guillaume Beslon. "Getting higher on rugged landscapes: Inversion mutations open access to fitter adaptive peaks in NK fitness landscapes." PLOS Computational Biology 18, no. 10 (October 31, 2022): e1010647. http://dx.doi.org/10.1371/journal.pcbi.1010647.

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Molecular evolution is often conceptualised as adaptive walks on rugged fitness landscapes, driven by mutations and constrained by incremental fitness selection. It is well known that epistasis shapes the ruggedness of the landscape’s surface, outlining their topography (with high-fitness peaks separated by valleys of lower fitness genotypes). However, within the strong selection weak mutation (SSWM) limit, once an adaptive walk reaches a local peak, natural selection restricts passage through downstream paths and hampers any possibility of reaching higher fitness values. Here, in addition to the widely used point mutations, we introduce a minimal model of sequence inversions to simulate adaptive walks. We use the well known NK model to instantiate rugged landscapes. We show that adaptive walks can reach higher fitness values through inversion mutations, which, compared to point mutations, allows the evolutionary process to escape local fitness peaks. To elucidate the effects of this chromosomal rearrangement, we use a graph-theoretical representation of accessible mutants and show how new evolutionary paths are uncovered. The present model suggests a simple mechanistic rationale to analyse escapes from local fitness peaks in molecular evolution driven by (intragenic) structural inversions and reveals some consequences of the limits of point mutations for simulations of molecular evolution.
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Reia, Sandro M., and Paulo R. A. Campos. "Analysis of statistical correlations between properties of adaptive walks in fitness landscapes." Royal Society Open Science 7, no. 1 (January 2020): 192118. http://dx.doi.org/10.1098/rsos.192118.

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The fitness landscape metaphor has been central in our way of thinking about adaptation. In this scenario, adaptive walks are idealized dynamics that mimic the uphill movement of an evolving population towards a fitness peak of the landscape. Recent works in experimental evolution have demonstrated that the constraints imposed by epistasis are responsible for reducing the number of accessible mutational pathways towards fitness peaks. Here, we exhaustively analyse the statistical properties of adaptive walks for two empirical fitness landscapes and theoretical NK landscapes. Some general conclusions can be drawn from our simulation study. Regardless of the dynamics, we observe that the shortest paths are more regularly used. Although the accessibility of a given fitness peak is reasonably correlated to the number of monotonic pathways towards it, the two quantities are not exactly proportional. A negative correlation between predictability and mean path divergence is established, and so the decrease of the number of effective mutational pathways ensures the convergence of the attraction basin of fitness peaks. On the other hand, other features are not conserved among fitness landscapes, such as the relationship between accessibility and predictability.
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Bajić, Djordje, Jean C. C. Vila, Zachary D. Blount, and Alvaro Sánchez. "On the deformability of an empirical fitness landscape by microbial evolution." Proceedings of the National Academy of Sciences 115, no. 44 (October 15, 2018): 11286–91. http://dx.doi.org/10.1073/pnas.1808485115.

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A fitness landscape is a map between the genotype and its reproductive success in a given environment. The topography of fitness landscapes largely governs adaptive dynamics, constraining evolutionary trajectories and the predictability of evolution. Theory suggests that this topography can be deformed by mutations that produce substantial changes to the environment. Despite its importance, the deformability of fitness landscapes has not been systematically studied beyond abstract models, and little is known about its reach and consequences in empirical systems. Here we have systematically characterized the deformability of the genome-wide metabolic fitness landscape of the bacterium Escherichia coli. Deformability is quantified by the noncommutativity of epistatic interactions, which we experimentally demonstrate in mutant strains on the path to an evolutionary innovation. Our analysis shows that the deformation of fitness landscapes by metabolic mutations rarely affects evolutionary trajectories in the short range. However, mutations with large environmental effects produce long-range landscape deformations in distant regions of the genotype space that affect the fitness of later descendants. Our results therefore suggest that, even in situations in which mutations have strong environmental effects, fitness landscapes may retain their power to forecast evolution over small mutational distances despite the potential attenuation of that power over longer evolutionary trajectories. Our methods and results provide an avenue for integrating adaptive and eco-evolutionary dynamics with complex genetics and genomics.
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Bertram, Jason, and Joanna Masel. "Evolution Rapidly Optimizes Stability and Aggregation in Lattice Proteins Despite Pervasive Landscape Valleys and Mazes." Genetics 214, no. 4 (February 27, 2020): 1047–57. http://dx.doi.org/10.1534/genetics.120.302815.

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The “fitness” landscapes of genetic sequences are characterized by high dimensionality and “ruggedness” due to sign epistasis. Ascending from low to high fitness on such landscapes can be difficult because adaptive trajectories get stuck at low-fitness local peaks. Compounding matters, recent theoretical arguments have proposed that extremely long, winding adaptive paths may be required to reach even local peaks: a “maze-like” landscape topography. The extent to which peaks and mazes shape the mode and tempo of evolution is poorly understood, due to empirical limitations and the abstractness of many landscape models. We explore the prevalence, scale, and evolutionary consequences of landscape mazes in a biophysically grounded computational model of protein evolution that captures the “frustration” between “stability” and aggregation propensity. Our stability-aggregation landscape exhibits extensive sign epistasis and local peaks galore. Although this frequently obstructs adaptive ascent to high fitness and virtually eliminates reproducibility of evolutionary outcomes, many adaptive paths do successfully complete the ascent from low to high fitness, with hydrophobicity a critical mediator of success. These successful paths exhibit maze-like properties on a global landscape scale, in which taking an indirect path helps to avoid low-fitness local peaks. This delicate balance of “hard but possible” adaptation could occur more broadly in other biological settings where competing interactions and frustration are important.
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Wilke, Claus O., and Thomas Martinetz. "Adaptive walks on time-dependent fitness landscapes." Physical Review E 60, no. 2 (August 1, 1999): 2154–59. http://dx.doi.org/10.1103/physreve.60.2154.

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Hadany, L., and T. Beker. "Fitness-associated recombination on rugged adaptive landscapes." Journal of Evolutionary Biology 16, no. 5 (September 2003): 862–70. http://dx.doi.org/10.1046/j.1420-9101.2003.00586.x.

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Dissertations / Theses on the topic "Adaptive or fitness landscapes"

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SERRELLI, EMANUELE. "Adaptive landscapes: a case study of metaphors, models, and synthesis in evolutionary biology." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2011. http://hdl.handle.net/10281/19338.

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This dissertation brings a contribution to the philosophical debate on adaptive landscapes, an influent "model" or "metaphor" in evolutionary biology. Some elements of innovation are: the distinction between native and migrant metaphor; a processual and communicational idea on what the Modern Synthesis was, and on what role a metaphor could have played in it; a view (taken by Richard Lewontin) of the disunity and theoretical structure of population genetics; the distinction between “adaptive surfaces” (mainly metaphors) and “combination spaces”, two terms normally conflated in the word “landscape”; an analysis of what bridges (including heuristics) may be cast between equations of gene frequency and the genotype space that, due to its huge dimensionality, cannot be handled by mathematics; a specified vocabulary to be used to clear the adaptive landscapes debate, accompanied by a plea in favor of a pragmatic approach - for example, the plurality of available notions of model forces us to choose one notion and see where it brings, otherwise we get stuck in confused, endless debates; an updated analytical comment of recent landscapes - Dobzhansky, Simpson, Dawkins but also the proliferation of combination spaces used in evolutionary biology to address a great variety of problems; the vision (got by Sergey Gavrilets) of a patchwork of tools finally making Mendelian population suitable model also for speciation; the exact position of holey landscapes in this patchwork, and the idea that scientists’s questions - like “how possibly” questions - matter in accessing this patchwork and in deciding “what explains” and “what describes” what in the world; the direct response to some mistakes Massimo Pigliucci made, I think, in his assessment of the adaptive landscape; an analysis of the Extended Evolutionary Synthesis project at its present stage, and some reflections on the conditions that will allow such a project to give a fair treatment and a good position to tools from the past, like the adaptive landscapes.
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Meer, Margarita V. 1986. "Exploring fitness landscapes." Doctoral thesis, Universitat Pompeu Fabra, 2015. http://hdl.handle.net/10803/402192.

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Fitness landscape is a concept, which describes the dependence of phenotype on genotype. It was proposed almost a hundred years ago but only recent burst of technologies finally allowed exploring it. We studied different aspects of fitness landscape applying both: computational and experimental approaches. Using mammalian mitochondrial tRNAs we proved that evolution can proceed not only along the ridges of high fitness but also cross the low fitness valleys. Functional analysis of more than 56 000 mutants of green fluorescent protein from Aequorea victoria (avGFP) allowed us to describe local fitness landscape around a particular fitness peak. In addition to this we studied a case of population being on a slope – genetic code is undergoing changes in Methanosarcina making them stay in sub-optimum.
El paisaje adaptativo (fitness landscape) es un concepto que describe la dependencia del fenotipo en el genotipo. Hace mas de cien años que éste concepto fue propuesto, pero es sólo con la reciente expansión de tecnologías que finalmente ha podido ser explorado. Hemos estudiado diferentes aspectos del paisaje adaptativo aplicando tanto procedimientos computacionales como experimentales. Utilizando tRNAs mitocondriales de mamíferos hemos comprobado que la evolución puede proceder no sólo a lo largo de las crestas de elevado fitness sino también a través de los valles con reducido fitness. Análisis funcional de mas de 56000 mutantes de la proteína verde fuorescente de Aequorea Victoria (avGFP) nos permitió describir el paisaje adaptativo local alrededor de un punto máximo específico de fitness. Mas aún, hemos estudiado un caso de una población en una pendiente – el código genético está atravesando cambios en Methanosarcina quedándose en sub-óptimo.
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Di, Pietro Anthony. "Optimising evolutionary strategies for problems with varying noise strength." University of Western Australia. School of Computer Science and Software Engineering, 2007. http://theses.library.uwa.edu.au/adt-WU2007.0210.

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For many real-world applications of evolutionary computation, the fitness function is obscured by random noise. This interferes with the evaluation and selection processes and adversely affects the performance of the algorithm. Noise can be effectively eliminated by averaging a large number of fitness samples for each candidate, but the number of samples used per candidate (the resampling rate) required to achieve this is usually prohibitively large and time-consuming. Hence there is a practical need for algorithms that handle noise without eliminating it. Moreover, the amount of noise (noise strength and distribution) may vary throughout the search space, further complicating matters. We study noisy problems for which the noise strength varies throughout the search space. Such problems have generally been ignored by previous work, which has instead generally focussed on the specific case where the noise strength is the same at all points in the search domain. However, this need not be the case, and indeed this assumption is false for many applications. For example, in games of chance such as Poker, some strategies may be more conservative than others and therefore less affected by the inherent noise of the game. This thesis makes three significant contributions in the field of noisy fitness functions: We present the concept of dynamic resampling. Dynamic resampling is a technique that varies the resampling rate based on the noise strength and fitness for each candidate individually. This technique is designed to exploit the variation in noise strength and fitness to yield a more efficient algorithm. We present several dynamic resampling algorithms and give results that show that dynamic resampling can perform significantly better than the standard resampling technique that is usually used by the optimisation community, and that dynamic resampling algorithms that vary their resampling rates based on both noise strength and fitness can perform better than algorithms that vary their resampling rate based on only one of the above. We study a specific class of noisy fitness functions for which we counterintuitively find that it is better to use a higher resampling rate in regions of lower noise strength, and vice versa. We investigate how the evolutionary search operates on such problems, explain why this is the case, and present a hypothesis (with supporting evidence) for classifying such problems. We present an adaptive engine that automatically tunes the noise compensation parameters of the search during the run, thereby eliminating the need for the user to choose these parameters ahead of time. This means that our techniques can be readily applied to real-world problems without requiring the user to have specialised domain knowledge of the problem that they wish to solve. These three major contributions present a significant addition to the body of knowledge for noisy fitness functions. Indeed, this thesis is the first work specifically to examine the implications of noise strength that varies throughout the search domain for a variety of noise landscapes, and thus starts to fill a large void in the literature on noisy fitness functions.
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Karlsen, Ero Stig. "Learning and Evolution in Complex Fitness Landscapes." Thesis, Norwegian University of Science and Technology, Department of Computer and Information Science, 2007. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-8712.

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The Baldwin effect is the notion that life time adaptation can speed up evolution by 1) identifying good traits and 2) by genetic assimilation inscribing the traits in the population genetically. This thesis investigates the Baldwin effect by giving an introduction to its history, its current status in evolutionary biology and by reviewing some important experiments on the Baldwin effect in artificial life. It is shown that the Baldwin effect is perceived differently in the two fields; in evolutionary biology the phenomenon is surrounded by controversy, while the approach in artificial life seems to be more straight forward. Numerous computer simulations of the Baldwin effect have been conducted, and most report positive findings. I argue that the Baldwin effect has been interpreted differently in the literature, and that a more well-defined approach is needed. An experiment is performed where the effect of learning on evolution is observed in fitness landscapes of different complexity and with different learning costs. It is shown that the choice of operators and parameter settings are important when assessing the Baldwin effect in computer simulations. In particular I find that mutation has an important impact on the Baldwin effect. I argue that today's computer simulations are too abstract to serve as empirical evidence for the Baldwin effect, but that they nevertheless can be valuable indications of the phenomenon in nature. To assure the soundness of experiments on the Baldwin effect, the assumptions and choices made in the implementations need to be clarified and critically discussed. One important aspect is to compare the different experiments and their interpretations in an attempt to assess the coherence between the different simulations.

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Herrmann, Sebastian [Verfasser]. "Complex network analysis of fitness landscapes / Sebastian Herrmann." Mainz : Universitätsbibliothek Mainz, 2017. http://d-nb.info/1122760159/34.

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Barnett, Lionel. "Evolutionary search on fitness landscapes with neutral networks." Thesis, University of Sussex, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.288614.

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Hietpas, Ryan T. "Experimental Illumination of Comprehensive Fitness Landscapes: A Dissertation." eScholarship@UMMS, 2013. https://escholarship.umassmed.edu/gsbs_diss/667.

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Evolution is the single cohesive logical framework in which all biological processes may exist simultaneously. Incremental changes in phenotype over imperceptibly large timescales have given rise to the enormous diversity of life we witness on earth both presently and through the natural record. The basic unit of evolution is mutation, and by perturbing biological processes, mutations may alter the fitness of an individual. However, the fitness effect of a mutation is difficult to infer from historical record, and complex to obtain experimentally in an efficient and accurate manner. We have recently developed a high throughput method to iteratively mutagenize regions of essential genes in yeast and subsequently analyze individual mutant fitness termed Exceedingly Methodical and Parallel Investigation of Randomized Individual Codons (EMPIRIC). Utilizing this technique as exemplified in Chapters II and III, it is possible to determine the fitness effects of all possible point mutations in parallel through growth competition followed by a high throughput sequencing readout. We have employed this technique to determine the distribution of fitness effects in a nine amino acid region of the Hsp90 gene of S. cerevisiae under elevated temperature, and found the bimodal distribution of fitness effects to be remarkably consistent with near-neutral theory. Comparing the measured fitness effects of mutants to the natural record, phylogenetic alignments appear to be a poor predictor of experimental fitness. In Chapter IV, to further interrogate the properties of this region, library competition under conditions of elevated temperature and salinity were performed to study the potential of protein adaptation. Strikingly, whereas both optimal and elevated temperatures produced no statistically significant beneficial mutations, under conditions of elevated salinity, adaptive mutations appear with fitness advantages up to 8% greater than wild type. Of particular interest, mutations conferring fitness benefits under conditions of elevated salinity almost always experience a fitness defect in other experimental conditions, indicating these mutations are environmentally specialized. Applying the experimental fitness measurements to long standing theoretical predictions of adaptation, our results are remarkably consistent with Fisher’s Geometric Model of protein evolution. Epistasis between mutations can have profound effects on evolutionary trajectories. Although the importance of epistasis has been realized since the early 1900s, the interdependence of mutations is difficult to study in vivo due to the stochastic and constant nature of background mutations. In Chapter V, utilizing the EMPIRIC methodology allows us to study the distribution of fitness effects in the context of mutant genetic backgrounds with minimal influence from unintended background mutations. By analyzing intragenic epistatic interactions, we uncovered a complex interplay between solvent shielded structural residues and solvent exposed hydrophobic surface in the amino acid 582-590 region of Hsp90. Additionally, negative epistasis appears to be negatively correlated with mutational promiscuity while additive interactions are positively correlated, indicating potential avenues for proteins to navigate fitness ‘valleys’. In summary, the work presented in this dissertation is focused on applying experimental context to the theory-rich field of evolutionary biology. The development and implementation of a novel methodology for the rapid and accurate assessment of organismal fitness has allowed us to address some of the most basic processes of evolution including adaptation and protein expression level. Through the work presented here and by investigators across the world, the application of experimental data to evolutionary theory has the potential to improve drug design and human health in general, as well as allow for predictive medicine in the coming era of personalized medicine.
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Hietpas, Ryan T. "Experimental Illumination of Comprehensive Fitness Landscapes: A Dissertation." eScholarship@UMMS, 2006. http://escholarship.umassmed.edu/gsbs_diss/667.

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Evolution is the single cohesive logical framework in which all biological processes may exist simultaneously. Incremental changes in phenotype over imperceptibly large timescales have given rise to the enormous diversity of life we witness on earth both presently and through the natural record. The basic unit of evolution is mutation, and by perturbing biological processes, mutations may alter the fitness of an individual. However, the fitness effect of a mutation is difficult to infer from historical record, and complex to obtain experimentally in an efficient and accurate manner. We have recently developed a high throughput method to iteratively mutagenize regions of essential genes in yeast and subsequently analyze individual mutant fitness termed Exceedingly Methodical and Parallel Investigation of Randomized Individual Codons (EMPIRIC). Utilizing this technique as exemplified in Chapters II and III, it is possible to determine the fitness effects of all possible point mutations in parallel through growth competition followed by a high throughput sequencing readout. We have employed this technique to determine the distribution of fitness effects in a nine amino acid region of the Hsp90 gene of S. cerevisiae under elevated temperature, and found the bimodal distribution of fitness effects to be remarkably consistent with near-neutral theory. Comparing the measured fitness effects of mutants to the natural record, phylogenetic alignments appear to be a poor predictor of experimental fitness. In Chapter IV, to further interrogate the properties of this region, library competition under conditions of elevated temperature and salinity were performed to study the potential of protein adaptation. Strikingly, whereas both optimal and elevated temperatures produced no statistically significant beneficial mutations, under conditions of elevated salinity, adaptive mutations appear with fitness advantages up to 8% greater than wild type. Of particular interest, mutations conferring fitness benefits under conditions of elevated salinity almost always experience a fitness defect in other experimental conditions, indicating these mutations are environmentally specialized. Applying the experimental fitness measurements to long standing theoretical predictions of adaptation, our results are remarkably consistent with Fisher’s Geometric Model of protein evolution. Epistasis between mutations can have profound effects on evolutionary trajectories. Although the importance of epistasis has been realized since the early 1900s, the interdependence of mutations is difficult to study in vivo due to the stochastic and constant nature of background mutations. In Chapter V, utilizing the EMPIRIC methodology allows us to study the distribution of fitness effects in the context of mutant genetic backgrounds with minimal influence from unintended background mutations. By analyzing intragenic epistatic interactions, we uncovered a complex interplay between solvent shielded structural residues and solvent exposed hydrophobic surface in the amino acid 582-590 region of Hsp90. Additionally, negative epistasis appears to be negatively correlated with mutational promiscuity while additive interactions are positively correlated, indicating potential avenues for proteins to navigate fitness ‘valleys’. In summary, the work presented in this dissertation is focused on applying experimental context to the theory-rich field of evolutionary biology. The development and implementation of a novel methodology for the rapid and accurate assessment of organismal fitness has allowed us to address some of the most basic processes of evolution including adaptation and protein expression level. Through the work presented here and by investigators across the world, the application of experimental data to evolutionary theory has the potential to improve drug design and human health in general, as well as allow for predictive medicine in the coming era of personalized medicine.
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Lu, Guanzhou. "Characterising fitness landscapes with fitness-probability cloud and its applications to algorithm configuration." Thesis, University of Birmingham, 2014. http://etheses.bham.ac.uk//id/eprint/4756/.

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Metaheuristics are approximation optimisation techniques widely applied to solve complex optimisation problems. Despite a large number of developed metaheuristic algorithms, a limited amount of work has been done to understand on which kinds of problems the proposed algorithm will perform well or poorly and why. A useful solution to this dilemma is to use fitness landscape analysis to gain an in-depth understanding of which algorithms, or algorithm variants are best suited for solving which kinds of problem instances, even to dynamically determine the best algorithm configuration during different stages of a search algorithm. This thesis for the first time bridges the gap between fitness landscape analysis and algorithm configuration, i.e., finding the best suited configuration of a given algorithm for solving a particular problem instance. Studies in this thesis contribute to the following: a. Developing a novel and effective approach to characterise fitness landscapes and measure problem difficulty with respect to algorithms. b. Incorporating fitness landscape analysis in building a generic (problem-independent) approach, which can perform automatic algorithm configuration on a per-instance base, and in designing novel and effective algorithm configurations. c. Incorporating fitness landscape analysis in establishing a generic framework for designing adaptive heuristic algorithms.
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Manukyan, Narine. "Analysis and Modeling of Quality Improvement on Clinical Fitness Landscapes." ScholarWorks @ UVM, 2014. http://scholarworks.uvm.edu/graddis/253.

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Widespread unexplained variations in clinical practices and patient outcomes, together with rapidly growing availability of data, suggest major opportunities for improving the quality of medical care. One way that healthcare practitioners try to do that is by participating in organized healthcare quality improvement collaboratives (QICs). In QICs, teams of practitioners from different hospitals exchange information on clinical practices, with the aim of improving health outcomes at their own institutions. However, what works in one hospital may not work in others with different local contexts, due to non-linear interactions among various demographics, treatments, and practices. I.e., the clinical landscape is a complex socio-technical system that is difficult to search. In this dissertation we develop methods for analysis and modeling of complex systems, and apply them to the problem of healthcare improvement. Searching clinical landscapes is a multi-objective dynamic problem, as hospitals simultaneously optimize for multiple patient outcomes. We first discuss a general method we developed for finding which changes in features may be associated with various changes in outcomes at different points in time with different delays in affect. This method correctly inferred interactions on synthetic data, however the complexity and incompleteness of the real hospital dataset available to us limited the usefulness of this approach. We then discuss an agent-based model (ABM) of QICs to show that teams comprising individuals from similar institutions outperform those from more diverse institutions, under nearly all conditions, and that this advantage increases with the complexity of the landscape and the level of noise in assessing performance. We present data from a network of real hospitals that provides encouraging evidence of a high degree of similarity in clinical practices among hospitals working together in QIC teams. Based on model outcomes, we propose a secure virtual collaboration system that would allow hospitals to efficiently identify potentially better practices in use at other institutions similar to theirs, without any institutions having to sacrifice the privacy of their own data. To model the search for quality improvement in clinical fitness landscapes, we need benchmark landscapes with tunable feature interactions. NK landscapes have been the classic benchmarks for modeling landscapes with epistatic interactions, but the ruggedness is only tunable in discrete jumps. Walsh polynomials are more finely tunable than NK landscapes, but are only defined on binary alphabets and, in general, have unknown global maximum and minimum. We define a different subset of interaction models that we dub as NM landscapes. NM landscapes are shown to have smoothly tunable ruggedness and difficulty and known location and value of global maxima. With additional constraints, we can also determine the location and value of the global minima. The proposed NM landscapes can be used with alphabets of any arity, from binary to real-valued, without changing the complexity of the landscape. NM landscapes are thus useful models for simulating clinical landscapes with binary or real decision variables and varying number of interactions. NM landscapes permit proper normalization of fitnesses so that search results can be fairly averaged over different random landscapes with the same parameters, and fairly compared between landscapes with different parameters. In future work we plan to use NM landscapes as benchmarks for testing various algorithms that can discover epistatic interactions in real world datasets.
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Books on the topic "Adaptive or fitness landscapes"

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Colfer, Carol J. Pierce, Ravi Prabhu, and Anne M. Larson. Adaptive Collaborative Management in Forest Landscapes. London: Routledge, 2021. http://dx.doi.org/10.4324/9781003197256.

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The Geometry of Evolution: Adaptive Landscapes and Theoretical Morphospaces. Cambridge, UK: Cambridge University Press, 2007.

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McGhee, George R. The geometry of evolution: Adaptive landscapes and theoretical morphospaces. Cambridge, UK: Cambridge University Press, 2007.

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Fitness landscapes and the origin of species. Princeton, N.J: Princeton University Press, 2004.

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Richter, Hendrik, and Andries Engelbrecht, eds. Recent Advances in the Theory and Application of Fitness Landscapes. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-41888-4.

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1965-, Williams Allison, ed. Therapeutic landscapes. Aldershot, England: Ashgate, 2007.

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Bayesian adaptive methods for clinical trials. Boca Raton: Chapman & Hall/CRC, 2011.

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service), SpringerLink (Online, ed. Innate and Adaptive Immunity in the Tumor Microenvironment. Dordrecht: Springer Science + Business Media, LLC, 2008.

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Handbook of adaptive designs in pharmaceutical and clinical development. Boca Raton: CRC Press, 2011.

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Shamoon, Patwari, and Tang, Bo (Bo Ming), 1983-, eds. Learning from Delhi: Dispersed initiatives in changing urban landscapes. Farnham: Ashgate, 2010.

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Book chapters on the topic "Adaptive or fitness landscapes"

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Crossley, Matthew, Andy Nisbet, and Martyn Amos. "Fitness Landscape-Based Characterisation of Nature-Inspired Algorithms." In Adaptive and Natural Computing Algorithms, 110–19. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37213-1_12.

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Reeves, Colin R. "Fitness Landscapes." In Search Methodologies, 681–705. Boston, MA: Springer US, 2013. http://dx.doi.org/10.1007/978-1-4614-6940-7_22.

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Adami, Christoph. "Fitness Landscapes." In Introduction to Artificial Life, 199–223. New York, NY: Springer New York, 1998. http://dx.doi.org/10.1007/978-1-4612-1650-6_8.

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Langdon, William B., and Riccardo Poli. "Fitness Landscapes." In Foundations of Genetic Programming, 17–26. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-662-04726-2_2.

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Schuster, Peter. "Quasispecies on Fitness Landscapes." In Current Topics in Microbiology and Immunology, 61–120. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/82_2015_469.

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Peliti, Luca. "Fitness Landscapes and Evolution." In Physics of Biomaterials: Fluctuations, Selfassembly and Evolution, 287–308. Dordrecht: Springer Netherlands, 1996. http://dx.doi.org/10.1007/978-94-009-1722-4_13.

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Hénaux, Vincent, Adrien Goëffon, and Frédéric Saubion. "Evolving Fitness Landscapes with Complementary Fitness Functions." In Lecture Notes in Computer Science, 110–20. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-45715-0_9.

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Richter, Hendrik. "Fitness Landscapes and Evolutionary Dynamics." In Advances in Intelligent Systems and Computing, 5–8. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-33227-2_2.

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Reeves, Colin R. "Fitness Landscapes and Evolutionary Algorithms." In Lecture Notes in Computer Science, 3–20. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/10721187_1.

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Langdon, W. B. "Convergence of Program Fitness Landscapes." In Genetic and Evolutionary Computation — GECCO 2003, 1702–14. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-45110-2_63.

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Conference papers on the topic "Adaptive or fitness landscapes"

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Paperin, Greg, David Green, Alan Dorin, Tuan D. Pham, and Xiaobo Zhou. "Fitness Landscapes in Individual-Based Simulation Models of Adaptive Radiation." In COMPUTATIONAL MODELS FOR LIFE SCIENCES/CMLS '07. AIP, 2007. http://dx.doi.org/10.1063/1.2816631.

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Owen, Alan, and Inman Harvey. "Adapting Particle Swarm Optimisation for Fitness Landscapes with Neutrality." In 2007 IEEE Swarm Intelligence Symposium. IEEE, 2007. http://dx.doi.org/10.1109/sis.2007.367946.

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Pei, Yan, and Hideyuki Takagi. "Fitness Landscape Approximation by Adaptive Support Vector Regression with Opposition-Based Learning." In 2013 IEEE International Conference on Systems, Man and Cybernetics (SMC 2013). IEEE, 2013. http://dx.doi.org/10.1109/smc.2013.230.

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Kuk, Josiel, Richard Goncalves, and Aurora Pozo. "Combining Fitness Landscape Analysis and Adaptive Operator Selection in Multi and Many-Objective Optimization." In 2019 8th Brazilian Conference on Intelligent Systems (BRACIS). IEEE, 2019. http://dx.doi.org/10.1109/bracis.2019.00094.

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Verel, Sébastien. "Fitness landscapes and graphs." In the 11th annual conference companion. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1570256.1570431.

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Verel, Sebastien. "Fitness landscapes and graphs." In Proceeding of the fifteenth annual conference companion. New York, New York, USA: ACM Press, 2013. http://dx.doi.org/10.1145/2464576.2480804.

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Verel, Sébastien. "Fitness landscapes and graphs." In the fourteenth international conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2330784.2330927.

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Amirghasemi, Mehrdad, and Reza Zamani. "The Roles of Evolutionary Computation, Fitness Landscape, Constructive Methods and Local Searches in the Development of Adaptive Systems for Infrastructure Planning." In International Symposium for Next Generation Infrastructure. University of Wollongong, SMART Infrastructure Facility, 2014. http://dx.doi.org/10.14453/isngi2013.proc.2.

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Troiano, L. "On aggregation of fitness landscapes." In 2010 Second World Congress on Nature and Biologically Inspired Computing (NaBIC 2010). IEEE, 2010. http://dx.doi.org/10.1109/nabic.2010.5716379.

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Verel, Sebastien, Arnaud Liefooghe, and Clarisse Dhaenens. "Set-based multiobjective fitness landscapes." In the 13th annual conference. New York, New York, USA: ACM Press, 2011. http://dx.doi.org/10.1145/2001576.2001681.

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Reports on the topic "Adaptive or fitness landscapes"

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Mai Phuong, Nguyen, Hanna North, Duong Minh Tuan, and Nguyen Manh Cuong. Assessment of women’s benefits and constraints in participating in agroforestry exemplar landscapes. World Agroforestry, 2021. http://dx.doi.org/10.5716/wp21015.pdf.

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Participating in the exemplar landscapes of the Developing and Promoting Market-Based Agroforestry and Forest Rehabilitation Options for Northwest Vietnam project has had positive impacts on ethnic women, such as increasing their networks and decision-making and public speaking skills. However, the rate of female farmers accessing and using project extension material or participating in project nurseries and applying agroforestry techniques was limited. This requires understanding of the real needs and interests grounded in the socio-cultural contexts of the ethnic groups living in the Northern Mountain Region in Viet Nam, who have unique social and cultural norms and values. The case studies show that agricultural activities are highly gendered: men and women play specific roles and have different, particular constraints and interests. Women are highly constrained by gender norms, access to resources, decision-making power and a prevailing positive-feedback loop of time poverty, especially in the Hmong community. A holistic, timesaving approach to addressing women’s daily activities could reduce the effects of time poverty and increase project participation. As women were highly willing to share project information, the project’s impacts would be more successful with increased participation by women through utilizing informal channels of communication and knowledge dissemination. Extension material designed for ethnic women should have less text and more visuals. Access to information is a critical constraint that perpetuates the norm that men are decision-makers, thereby, enhancing their perceived ownership, whereas women have limited access to information and so leave final decisions to men, especially in Hmong families. Older Hmong women have a Vietnamese (Kinh) language barrier, which further prevents them from accessing the project’s material. Further research into an adaptive framework that can be applied in a variety of contexts is recommended. This framework should prioritize time-saving activities for women and include material highlighting key considerations to maintain accountability among the project’s support staff.
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Michalak, Julia, Josh Lawler, John Gross, and Caitlin Littlefield. A strategic analysis of climate vulnerability of national park resources and values. National Park Service, September 2021. http://dx.doi.org/10.36967/nrr-2287214.

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The U.S. national parks have experienced significant climate-change impacts and rapid, on-going changes are expected to continue. Despite the significant climate-change vulnerabilities facing parks, relatively few parks have conducted comprehensive climate-change vulnerability assessments, defined as assessments that synthesize vulnerability information from a wide range of sources, identify key climate-change impacts, and prioritize vulnerable park resources (Michalak et al. In review). In recognition that funding and planning capacity is limited, this project was initiated to identify geographies, parks, and issues that are high priorities for conducting climate-change vulnerability assessments (CCVA) and strategies to efficiently address the need for CCVAs across all U.S. National Park Service (NPS) park units (hereafter “parks”) and all resources. To help identify priority geographies and issues, we quantitatively assessed the relative magnitude of vulnerability factors potentially affecting park resources and values. We identified multiple vulnerability factors (e.g., temperature change, wildfire potential, number of at-risk species, etc.) and sought existing datasets that could be developed into indicators of these factors. To be included in the study, datasets had to be spatially explicit or already summarized for individual parks and provide consistent data for at least all parks within the contiguous U.S. (CONUS). The need for consistent data across such a large geographic extent limited the number of datasets that could be included, excluded some important drivers of climate-change vulnerability, and prevented adequate evaluation of some geographies. The lack of adequately-scaled data for many key vulnerability factors, such as freshwater flooding risks and increased storm activity, highlights the need for both data development and more detailed vulnerability assessments at local to regional scales where data for these factors may be available. In addition, most of the available data at this scale were related to climate-change exposures, with relatively little data available for factors associated with climate-change sensitivity or adaptive capacity. In particular, we lacked consistent data on the distribution or abundance of cultural resources or accessible data on infrastructure across all parks. We identified resource types, geographies, and critical vulnerability factors that lacked data for NPS’ consideration in addressing data gaps. Forty-seven indicators met our criteria, and these were combined into 21 climate-change vulnerability factors. Twenty-seven indicators representing 12 vulnerability factors addressed climate-change exposure (i.e., projected changes in climate conditions and impacts). A smaller number of indictors measured sensitivity (12 indicators representing 5 vulnerability factors). The sensitivity indicators often measured park or landscape characteristics which may make resources more or less responsive to climate changes (e.g., current air quality) as opposed to directly representing the sensitivity of specific resources within the park (e.g., a particular rare species or type of historical structure). Finally, 6 indicators representing 4 vulnerability factors measured external adaptive capacity for living resources (i.e., characteristics of the park and/or surrounding landscape which may facilitate or impede species adaptation to climate changes). We identified indicators relevant to three resource groups: terrestrial living, aquatic living (including living cultural resources such as culturally significant landscapes, plant, or animal species) and non-living resources (including infrastructure and non-living cultural resources such as historic buildings or archeological sites). We created separate indicator lists for each of these resource groups and analyzed them separately. To identify priority geographies within CONUS,...
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Brandt, Leslie A., Cait Rottler, Wendy S. Gordon, Stacey L. Clark, Lisa O'Donnell, April Rose, Annamarie Rutledge, and Emily King. Vulnerability of Austin’s urban forest and natural areas: A report from the Urban Forestry Climate Change Response Framework. U.S. Department of Agriculture, Northern Forests Climate Hub, October 2020. http://dx.doi.org/10.32747/2020.7204069.ch.

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The trees, developed green spaces, and natural areas within the City of Austin’s 400,882 acres will face direct and indirect impacts from a changing climate over the 21st century. This assessment evaluates the vulnerability of urban trees and natural and developed landscapes within the City Austin to a range of future climates. We synthesized and summarized information on the contemporary landscape, provided information on past climate trends, and illustrated a range of projected future climates. We used this information to inform models of habitat suitability for trees native to the area. Projected shifts in plant hardiness and heat zones were used to understand how less common native species, nonnative species, and cultivars may tolerate future conditions. We also assessed the adaptability of planted and naturally occurring trees to stressors that may not be accounted for in habitat suitability models such as drought, flooding, wind damage, and air pollution. The summary of the contemporary landscape identifies major stressors currently threatening trees and forests in Austin. Major current threats to the region’s urban forest include invasive species, pests and disease, and development. Austin has been warming at a rate of about 0.4°F per decade since measurements began in 1938 and temperature is expected to increase by 5 to 10°F by the end of this century compared to the most recent 30-year average. Both increases in heavy rain events and severe droughts are projected for the future, and the overall balance of precipitation and temperature may shift Austin’s climate to be more similar to the arid Southwest. Species distribution modeling of native trees suggests that suitable habitat may decrease for 14 primarily northern species, and increase for four more southern species. An analysis of tree species vulnerability that combines model projections, shifts in hardiness and heat zones, and adaptive capacity showed that only 3% of the trees estimated to be present in Austin based on the most recent Urban FIA estimate were considered to have low vulnerability in developed areas. Using a panel of local experts, we also assessed the vulnerability of developed and natural areas. All areas were rated as having moderate to moderate-high vulnerability, but the underlying factors driving that vulnerability differed by natural community and between East and West Austin. These projected changes in climate and their associated impacts and vulnerabilities will have important implications for urban forest management, including the planting and maintenance of street and park trees, management of natural areas, and long-term planning.
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