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Relevant bibliographies by topics / Genetic Fitness

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Academic literature on the topic 'Genetic Fitness'

Author: Grafiati

Published: 4 June 2021

Last updated: 18 February 2022

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Journal articles on the topic "Genetic Fitness"

1

Montgomery, Hugh, and Latif Safari. "Genetic Basis of Physical Fitness." Annual Review of Anthropology 36, no. 1 (September 2007): 391–405. http://dx.doi.org/10.1146/annurev.anthro.36.081406.094333.

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Bouchard, C., T. Rankinen, L. Perusse, F. Booth, and S. Britton. "GENETIC DIFFERENCES, FITNESS AND PERFORMANCE." Medicine & Science in Sports & Exercise 34, no. 5 (May 2002): S46. http://dx.doi.org/10.1097/00005768-200205001-00248.

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Zhai, W., P. Kelly, and W. B. Gong. "Genetic algorithms with noisy fitness." Mathematical and Computer Modelling 23, no. 11-12 (June 1996): 131–42. http://dx.doi.org/10.1016/0895-7177(96)00068-4.

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Charlesworth, Brian. "Causes of natural variation in fitness: Evidence from studies of Drosophila populations." Proceedings of the National Academy of Sciences 112, no. 6 (January 8, 2015): 1662–69. http://dx.doi.org/10.1073/pnas.1423275112.

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DNA sequencing has revealed high levels of variability within most species. Statistical methods based on population genetics theory have been applied to the resulting data and suggest that most mutations affecting functionally important sequences are deleterious but subject to very weak selection. Quantitative genetic studies have provided information on the extent of genetic variation within populations in traits related to fitness and the rate at which variability in these traits arises by mutation. This paper attempts to combine the available information from applications of the two approaches to populations of the fruitfly Drosophila in order to estimate some important parameters of genetic variation, using a simple population genetics model of mutational effects on fitness components. Analyses based on this model suggest the existence of a class of mutations with much larger fitness effects than those inferred from sequence variability and that contribute most of the standing variation in fitness within a population caused by the input of mildly deleterious mutations. However, deleterious mutations explain only part of this standing variation, and other processes such as balancing selection appear to make a large contribution to genetic variation in fitness components in Drosophila.

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O’Brien, Anna M., Chandra N. Jack, Maren L. Friesen, and Megan E. Frederickson. "Whose trait is it anyways? Coevolution of joint phenotypes and genetic architecture in mutualisms." Proceedings of the Royal Society B: Biological Sciences 288, no. 1942 (January 13, 2021): 20202483. http://dx.doi.org/10.1098/rspb.2020.2483.

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Evolutionary biologists typically envision a trait’s genetic basis and fitness effects occurring within a single species. However, traits can be determined by and have fitness consequences for interacting species, thus evolving in multiple genomes. This is especially likely in mutualisms, where species exchange fitness benefits and can associate over long periods of time. Partners may experience evolutionary conflict over the value of a multi-genomic trait, but such conflicts may be ameliorated by mutualism’s positive fitness feedbacks. Here, we develop a simulation model of a host–microbe mutualism to explore the evolution of a multi-genomic trait. Coevolutionary outcomes depend on whether hosts and microbes have similar or different optimal trait values, strengths of selection and fitness feedbacks. We show that genome-wide association studies can map joint traits to loci in multiple genomes and describe how fitness conflict and fitness feedback generate different multi-genomic architectures with distinct signals around segregating loci. Partner fitnesses can be positively correlated even when partners are in conflict over the value of a multi-genomic trait, and conflict can generate strong mutualistic dependency. While fitness alignment facilitates rapid adaptation to a new optimum, conflict maintains genetic variation and evolvability, with implications for applied microbiome science.

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GUO, Guang-song, Dun-wei GONG, Guo-sheng HAO, and Yong ZHANG. "Interactive Genetic Algorithms with Fitness Adjustment." Journal of China University of Mining and Technology 16, no. 4 (December 2006): 480–84. http://dx.doi.org/10.1016/s1006-1266(07)60052-2.

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Takahashi, Yuma, Ryoya Tanaka, Daisuke Yamamoto, Suzuki Noriyuki, and Masakado Kawata. "Balanced genetic diversity improves population fitness." Proceedings of the Royal Society B: Biological Sciences 285, no. 1871 (January 17, 2018): 20172045. http://dx.doi.org/10.1098/rspb.2017.2045.

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Although genetic diversity within a population is suggested to improve population-level fitness and productivity, the existence of these effects is controversial because empirical evidence for an ecological effect of genetic diversity and the underlying mechanisms is scarce and incomplete. Here, we show that the natural single-gene behavioural polymorphism ( Rover and sitter ) in Drosophila melanogaster has a positive effect on population fitness. Our simple numerical model predicted that the fitness of a polymorphic population would be higher than that expected with two monomorphic populations, but only under balancing selection. Moreover, this positive diversity effect of genetic polymorphism was attributable to a complementarity effect, rather than to a selection effect. Our empirical tests using the behavioural polymorphism in D. melanogaster clearly supported the model predictions. These results provide direct evidence for an ecological effect of genetic diversity on population fitness and its condition dependence.

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Rankinen, Tuomo. "Genetic Influences on Fitness and Activity." Medicine & Science in Sports & Exercise 40, Supplement (May 2008): 65. http://dx.doi.org/10.1249/01.mss.0000321314.29517.2e.

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Vose, Michael D., and Alden H. Wright. "Simple Genetic Algorithms with Linear Fitness." Evolutionary Computation 2, no. 4 (December 1994): 347–68. http://dx.doi.org/10.1162/evco.1994.2.4.347.

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A general form of stochastic search is described (random heuristic search), and some of its general properties are proved. This provides a framework in which the simple genetic algorithm (SGA) is a special case. The framework is used to illuminate relationships between seemingly different probabilistic perspectives of SGA behavior. Next, the SGA is formalized as an instance of random heuristic search. The formalization then used to show expected population fitness is a Lyapunov function in the infinite population model when mutation is zero and fitness is linear. In particular, the infinite population algorithm must converge, and average population fitness increases from one generation to the next. The consequence for a finite population SGA is that the expected population fitness increases from one generation to the next. Moreover, the only stable fixed point of the expected next population operator corresponds to the population consisting entirely of the optimal string. This result is then extended by way of a perturbation argument to allow nonzero mutation.

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Reed, David H., and Richard Frankham. "Correlation between Fitness and Genetic Diversity." Conservation Biology 17, no. 1 (February 2003): 230–37. http://dx.doi.org/10.1046/j.1523-1739.2003.01236.x.

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Dissertations / Theses on the topic "Genetic Fitness"

1

Bancroft, David. "Genetic variation and fitness in Soay sheep." Thesis, University of Cambridge, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.338112.

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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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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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Ricketts, Huw John. "Molecular genetic biomarkers of reproductive fitness in earthworms." Thesis, Cardiff University, 2004. http://orca.cf.ac.uk/55966/.

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When ecotoxicologists assess the environmental impact of pollution they must pose a fundamental question. That is, is the toxicological data produced from any experiment ecologically relevant It has long been thought that a measure of survival of any organism is not sufficient to predict potential population effects. A more sensitive method is the measurement of sub-lethal endpoints, such as growth and reproduction. However, measurement of these parameters may not give an 'early warning' of the impact of complex pollutants within any ecosystem. Therefore, so-called biomarkers have been developed to fill this void. Biomarkers can be used at a number of organisational levels e.g. cellular, protein or DNA, but they all have the sensitivity to act as predictive tools in ecotoxicology and risk assessment. In the past twenty years earthworms have become model organisms in terrestrial ecotoxicology. This is mainly due to the critical role they play within the soil ecosystem in most parts of the world. Therefore the present study utilises three earthworm species (Eisenia fetida, Eisenia andrei and Lumbricus rubellus) to identify, characterise and validate molecular genetic biomarkers of reproduction. To isolate potential reproductive genes a subtractive library was created from the anterior and posterior segments of Lumbricus rubellus. A number of potential biomarker candidate genes were identified, but a putative sperm-specific antigen warranted special attention. The gene fragment of this putative sperm antigen was identified in all three earthworm species used in the study and its potential as a biomarker is discussed. Annetocin has previously been characterised as a member of the mammalian vasopressin/oxytocin superfamily of neuropeptides and has been shown to induce egg-laying behaviours in Eisenia fetida. The annetocin gene was isolated from the three earthworm species and shown to be expressed in the reproductive segments of Eisenia fetida. The expression levels of the annetocin gene were determined in earthworms exposed to metalliferous soils both in laboratory and semi-field exposures using quantitative PCR. A decrease in annetocin gene expression levels correlated with a similar decrease in cocoon production rates of Eisenia fetida after metal exposure. Upon exposure to the mammalian steroid hormones, 17/3-oestradiol and testosterone along with the synthetic oestrogen 17a-ethynylestradiol, annetocin gene expression levels in Eisenia andrei were elevated in some cases, suggesting a role for oestrogens in earthworm reproduction. Eisenia andrei were also exposed to bisphenol A and nonylphenol in artificial soils and annetocin gene expression was determined. Although toxic to Eisenia andrei these two (weakly oestrogenic) compounds did not affect annetocin gene expression. These data strongly suggest that annetocin plays a critical role in earthworm reproduction and that oestrogens may modulate the expression of this gene. The annetocin genomic structure was determined and three oestrogen-responsive elements were identified within the promoter of the gene in Eisenia fetida. What is more, the genomic structure of annetocin conformed to the three exon, two intron model of vasopressin/oxytocin superfamily neuropeptides.

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May, Shoshanna. "Fitness and genetic diversity in Bufo calamita populations." Thesis, University of Sussex, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.505908.

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The aims of this DPhil were the characterisation of major histocompatibility complex class II β loci in the amphibian species Bufo calamita, determination of fitness of four Bufo calamita populations and measurement of genetic diversity at both microsatellite loci and MHC class II β loci. The genetic diversity at microsatellite loci is considered to be neutral to selection and the genetic diversity seen at MHC loci is adaptive. Fitness in the four populations was measured using the known larval fitness traits age at metamorphosis, growth rates and survival. A 114 base pair section of MHC class II loci was characterised in this study. It was shown here that the diversity at neutral microsatellite markers was negatively correlated with adaptive MHC class II variation. No correlation was found between microsatellite HE and the larval fitness traits growth rate, survival and age at metamorphosis. However, MHC class II diversity was found to be associated with survival, and individuals that were heterozygous at both MHC loci had a significantly higher chance of survival than individuals homozygous at one or both of the two loci. A separate part of this DPhil project was the population genetics of six Irish Bufo calamita populations. The genetic structure was investigated using nine polymorphic microsatellite markers. It was found that all populations had similar and moderate levels of genetic diversity, comparable with those on the coast of north-west England. Toad populations were substantially differentiated, implying little migration between sites within historical times. Phylogenetics and estimates of divergence times supported the hypothesis that populations on the north coast of Dingle separated from those around Castlemaine Harbour many thousands of years ago, and are not recent introductions.

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Cooper, Jason. "Improving performance of genetic algorithms by using novel fitness functions." Thesis, Loughborough University, 2006. https://dspace.lboro.ac.uk/2134/2271.

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This thesis introduces Intelligent Fitness Functions and Partial Fitness Functions both of which can improve the performance of a genetic algorithm which is limited to a fixed run time. An Intelligent Fitness Function is defined as a fitness function with a memory. The memory is used to store information about individuals so that duplicate individuals do not need to have their fitness tested. Different types of memory (long and short term) and different storage strategies (fitness based, time base and frequency based) have been tested. The results show that an intelligent fitness function, with a time based long term memory improves the efficiency of a genetic algorithm the most. A Partial Fitness Function is defined as a fitness function that only partially tests the fitness of an individual at each generation. Thus only promising individuals get fully tested. Using a partial fitness function gives the genetic algorithm more evolutionary steps in the same length of time as a genetic algorithm using a normal fitness function. The results show that a genetic algorithm using a partial fitness function can achieve higher fitness levels than a genetic algorithm using a normal fitness function. Finally a genetic algorithm designed to solve a substitution cipher is compared to one equipped with an intelligent fitness function and another equipped with a partial fitness function. The genetic algorithm with the intelligent fitness function and the genetic algorithm with the partial fitness function both show a significant improvement over the genetic algorithm with a conventional fitness function.

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Haram, Per Magnus. "Genetic vs. Aquired fitness: Metabolic, Vascular and Cardiomyocyte Adaptations." Doctoral thesis, Norwegian University of Science and Technology, Department of Circulation and Medical Imaging, 2006. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-1921.

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Ali, Mohamed Medhat. "Studying the genetic determinants of Salmonella fitness in vivo." The Ohio State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=osu1397816634.

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Grieshop, Karl. "Sexual conflict, sexual selection, and genetic variance in fitness." Doctoral thesis, Uppsala universitet, Zooekologi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-327304.

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Understanding sex-specific genetic variance for fitness is of fundamental importance to our understanding of evolution. This thesis presents the findings of empirical investigations into sex-specific genetic variance in fitness. The findings are discussed in terms of their implications for our understanding of the classic evolutionary paradoxes of what maintains genetic variance in fitness and what maintains sexual reproduction, as well as more specific implications regarding adaptation and population viability. Males and females reproduce and accrue fitness in fundamentally different ways, which inevitably comes at a detriment to the fitness of individuals of the opposite sex. This is known as sexual conflict, and because males and females use largely the same genome to develop, grow and reproduce, a genetic tug-of-war ensues. Alternative alleles at sexually antagonistic (SA) genes have opposing fitness effects in males and females. The consequence of this genetic tug-of-war is that alternative allelic variants at SA loci can be maintained in the population. Such SA genetic variation can therefore maintain genetic variance for fitness. Variance in fitness can also be maintained by a constant influx of mutations with weakly deleterious effects and weak selection against them, in what is referred to as mutation-selection balance. Because the average deleterious mutation will be detrimental to both sexes, this source of genetic variance in fitness will have predominantly sexually concordant (SC) effects. This thesis uses a wild-caught population of the seed beetle Callosobruchus maculatus to investigate these two mechanisms of maintaining genetic variance in fitness, as well as the consequences they bear on adaptation, population viability, and the maintenance of sexual reproduction. Results largely support much of the theoretical expectations for sexual conflict, sexual selection and maintenance of genetic variance in fitness, as well as stimulate new thoughts and hypotheses about the nature of SA genetic variation and its interaction with weakly deleterious partially recessive mutations.
Vår kunskap om könsspecifik selektion och genetisk variation för fitness är central för förståelsen av evolutionära processer. I den här avhandligen presenteras resultaten av empiriska undersökningar av just könsspecifik genetisk variation för fitness. Resultaten diskuteras med fokus på deras betydelse för de klassiska evolutionära paradoxerna angående vad som bibehåller genetisk variation i fitness och varför organismer som förökar sig sexuellt är så vanliga, men även mer specifika konsekvenser för en populations anpassningsförmåga och livskraftighet avhandlas. Evolutionen har ofta gynnat olika reproduktiva strategier hos hannar och honor, och dessa strategier kan medföra kostnader för det motsatta könet. Den könskonflikt som uppstår på grund av detta kan också inbegripa en genetisk dragkamp eftersom könen delar genetisk arvsmassa men gynnas av olika anpassningar. Konsekvensen är att alternativa varianter av gener gynnas hos honor och hanar, vilket resulterar i en form av balanserande selektion som kan bibehålla genetisk variation i en population. Genetisk variation i fitness kan även upprätthållas genom en jämvikt mellan ett konstant inflöde av genetisk variation via mutationer med svagt negativ effekt och svag selektion mot dessa mutationer. Eftersom en negativ mutation normalt kommer vara skadlig för båda könen kommer den här typen av källa till genetisk variation i fitness ha liknande effekt hos könen. I arbetet med denna avhandlig har jag använt en vilt infångad population av fröbaggaen Callosobruchus maculatus för att undersöka dessa två underliggande mekanismer bakom upprätthållandet av genetisk variation för fitness, samt vilka potentiella konsekvenser de kan ha för en populations anpassningsförmåga och för bibehållandet av sexuell reproduktion. Resultaten i denna avhandling stödjer i stort många av de antaganden som ligger till grund för teorin om könskonflikter, sexuell selektion och vad som upprätthåller genetisk variation för fitness. Resultaten ger också upphov till nya idéer och hypoteser angående genetisk variation med könsspecifika effekter och dess interaktion med partiellt recessiva negativa mutationer.

The alternative abstract I uploaded should be used as the Swedish summary.

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Drahošová, Michaela. "Koevoluce prediktorů fitness v kartézském genetickém programování." Doctoral thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2017. http://www.nusl.cz/ntk/nusl-412587.

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Kartézské genetické programován (CGP) je evoluc inspirovaná metoda strojového učen, která je primárně určená pro automatizovaný návrh programů a čslicových obvodů. CGP je úspěšné v řešen mnoha úloh z reálného světa. Avšak k nalezen inovativnch řešen obvykle potřebuje značný výpočetn výkon. Každý kandidátn program navržený pomoc CGP mus být spuštěn, aby se zjistilo, do jaké mry tento program řeš zadaný problém, a mohla mu být přiřazena fitness hodnota. Právě vyhodnocen fitness bývá výpočetně nejnáročnějš část návrhu pomoc CGP. Tato práce se zabývá využitm koevoluce prediktorů fitness v CGP za účelem zrychlen procesu evolučnho návrhu prováděného pomoc CGP. Prediktor fitness je malá podmnožina trénovacch dat použvaná pro rychlý odhad fitness hodnoty namsto náročného vyhodnocen objektivn fitness hodnoty. Koevoluce prediktorů fitness je optimalizačn metoda modelován fitness, která snižuje náročnost a frekvenci výpočtu fitness. V této práci je koevolučn algoritmus přizpůsoben pro CGP a jsou představeny a zkoumány tři přstupy k zakódován prediktorů fitness. Představená metoda je experimentálně vyhodnocena v pěti úlohách symbolické regrese a v úloze návrhu obrazových filtrů. Výsledky experimentů ukazuj, že pomoc této metody lze významně snžit výpočetn čas, který CGP potřebuje pro řešen zkoumané třdy úloh.

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Books on the topic "Genetic Fitness"

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M, Malina Robert, and Pérusse Louis 1957-, eds. Genetics of fitness and physical performance. Champaign, IL: Human Kinetics, 1997.

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1933-, Simopoulos Artemis P., ed. Nutrition and fitness: Cultural, genetic, and metabolic aspects. Basel: Karger, 2008.

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Parker, James N., and Philip M. Parker. The official parent's sourcebook on aicardi syndrome. San Diego, CA: ICON Health Publications, 2003.

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Smith, Moyra. Translational research in genetics and genomics. Oxford: Oxford University Press, 2008.

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Smith, Moyra. Translational research in genetics and genomics. Oxford: Oxford University Press, 2008.

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1951-, Johnston Mark, ed. Genetic twists of fate. Cambridge, MA: MIT Press, 2010.

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1933-, Simopoulos Artemis P., and Pavlou Konstantinos N, eds. Nutrition and fitness: Diet, genes, physical activity, and health. Basel: Karger, 2001.

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

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Prista, António. O desafio de Calanga: Do lugar e das pessoas à aventura da ciência. Maputo, Moçambique: Facultade de Educac̥aõ Física e Desporto, 2010.

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Eric, Engel. Genomic imprinting and uniparental disomy in medicine: Clinical and molecular aspects. New York: Wiley-Liss, 2002.

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Book chapters on the topic "Genetic Fitness"

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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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Ekárt, Anikó. "Shorter Fitness Preserving Genetic Programs." In Lecture Notes in Computer Science, 73–83. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/10721187_5.

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Hill, William G., and Xu-Sheng Zhang. "Maintaining Genetic Variation in Fitness." In Adaptation and Fitness in Animal Populations, 59–81. Dordrecht: Springer Netherlands, 2009. http://dx.doi.org/10.1007/978-1-4020-9005-9_5.

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Howden, Reuben, Benjamin D. H. Gordon, and Ebony C. Gaillard. "Genetic Contributions to Cardiorespiratory Fitness." In Routledge Handbook of Sport and Exercise Systems Genetics, 187–99. Abingdon, Oxon ; New York, NY : Routledge, 2019.: Routledge, 2019. http://dx.doi.org/10.4324/9781315146287-19.

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Gibson, John P. "Livestock Genetic Resources: Preserving Genetic Adaptations for Future Use." In Adaptation and Fitness in Animal Populations, 229–32. Dordrecht: Springer Netherlands, 2009. http://dx.doi.org/10.1007/978-1-4020-9005-9_15.

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Schmidt, Michael, and Hod Lipson. "Age-Fitness Pareto Optimization." In Genetic Programming Theory and Practice VIII, 129–46. New York, NY: Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-7747-2_8.

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Ollivier, Louis, and Jean-Louis Foulley. "Managing Genetic Diversity, Fitness and Adaptation of Farm Animal Genetic Resources." In Adaptation and Fitness in Animal Populations, 201–27. Dordrecht: Springer Netherlands, 2009. http://dx.doi.org/10.1007/978-1-4020-9005-9_14.

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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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Slavov, V., and N. I. Nikolaev. "Fitness Landscapes and Inductive Genetic Programming." In Artificial Neural Nets and Genetic Algorithms, 414–18. Vienna: Springer Vienna, 1998. http://dx.doi.org/10.1007/978-3-7091-6492-1_91.

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Langdon, W. B., and R. Poli. "Genetic programming bloat with dynamic fitness." In Lecture Notes in Computer Science, 97–112. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/bfb0055931.

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Conference papers on the topic "Genetic Fitness"

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Hasegawa, Taku, Kaname Matsumura, Kaiki Tsuchie, Naoki Mori, and Keinosuke Matsumoto. "Novel virtual fitness evaluation framework for fitness landscape learning evolutionary computation." In GECCO '14: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2014. http://dx.doi.org/10.1145/2598394.2598496.

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Krawiec, Krzysztof, and PrzemysBaw Polewski. "Potential fitness for genetic programming." In the 2008 GECCO conference companion. New York, New York, USA: ACM Press, 2008. http://dx.doi.org/10.1145/1388969.1389043.

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Smith, Robert E., B. A. Dike, and S. A. Stegmann. "Fitness inheritance in genetic algorithms." In the 1995 ACM symposium. New York, New York, USA: ACM Press, 1995. http://dx.doi.org/10.1145/315891.316014.

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Lockett, Alan J. "Insights From Adversarial Fitness Functions." In FOGA '15: Foundations of Genetic Algorithms XIII. New York, NY, USA: ACM, 2015. http://dx.doi.org/10.1145/2725494.2725501.

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Langdon, William B. "Fitness first and fatherless crossover." In GECCO '21: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3449726.3459437.

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Biazzi, Renata B., André Fujita, and Daniel Y. Takahashi. "Predicting soft robot's locomotion fitness." In GECCO '21: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3449726.3459417.

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Johnson, Colin G., and John R. Woodward. "Fitness as Task-relevant Information Accumulation." In GECCO '15: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2015. http://dx.doi.org/10.1145/2739482.2768428.

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Ochoa, Gabriela, and Katherine Malan. "Recent advances in fitness landscape analysis." In GECCO '19: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3319619.3323383.

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Aleti, Aldeida, Katherine Malan, and Irene Moser. "Fitness landscape characterisation of optimisation problems." In GECCO '17: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3067695.3067720.

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Cleghorn, Christopher W., and Andries P. Engelbrecht. "Fitness-distance-ratio particle swarm optimization." In GECCO '17: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3071178.3071256.

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Reports on the topic "Genetic Fitness"

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Ankenbrandt, C. A., B. P. Buckles, F. E. Petry, and M. Lybanon. Ocean Feature Recognition Using Genetic Algorithms with Fuzzy Fitness Functions (GA/F3). Fort Belvoir, VA: Defense Technical Information Center, July 1989. http://dx.doi.org/10.21236/ada230891.

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Di Giulio, Richard T. Adaptation of a Population of Fundulus heteroclitus to a Creosote-Contaminated Environment: Mechanisms, Genetic Consequences and Fitness Trade-Offs. Fort Belvoir, VA: Defense Technical Information Center, September 2005. http://dx.doi.org/10.21236/ada437526.

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