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Robustness and evolvability of biological systems
Published in Karthik Raman, An Introduction to Computational Systems Biology, 2021
While the genotype denotes the genetic makeup, the phenotype refers to higher-level observable characteristics or traits of an organism. At the molecular level, features such as protein structures, RNA structures or folds can be regarded as molecular phenotypes. At a higher level of organisation, namely the network level, more complex phenotypes can be considered. Table 13.1 lists some examples of genotype–phenotype mapping from RNA to metabolic networks to artificial human-made systems such as digital circuits. Once we determine the mapping between genotype and phenotype—this could be via an experiment, or theoretically, via computation—we can unravel the various genotype networks that span the genotype space. Figure 13.2b shows phenotypes mapped on to genotypes using a variety of colours. Evidently, the genotype space is laced with numerous genotype networks, of different sizes and connectivities.
Mine ventilation system planning esing genetic algorithms
Published in Vladimír Strakoš, Vladimír Kebo, Radim Farana, Lubomír Smutný, Mine Planning and Equipment Selection 1997, 2020
N. M. Lilić, R. M. Stanković, I. M. Obradović
A genotype is an explicit genetic structure of chromosomes, while a phenotype is the real, physical representation of the genotype. The objective function is the function being optimized, i.e. the function whose minimum or maximum is required. The feasibility measure, i.e. the fitness of an individual demonstrates, in the optimization case, how well that individual, i.e. the solution represented by the chromosome optimizes the objective function. In the case of minimization, the fitness value is inversely proportional to the value of the objective function, and in the maximization task, the values of the objective function and fitness are proportional. A chromosome can contain groups of genes with common characteristics which are called schemes, an sometimes pools.
Autonomous Mental Development
Published in Bogdan M. Wilamowski, J. David Irwin, Intelligent Systems, 2018
A human being starts to develop from the time of conception. At that time, a single cell called a zygote is formed. In biology, the term genotype refers to all or part of the genetic constitution of an organism. The term phenotype refers to all or part of the visible properties of an organism that are produced through the interaction between the genotype and the environment. In the zygote, all the genetic constitution is called genome, which mostly resides in the nucleus of a cell. At the conception of a new human life, a biological program called the developmental program starts to run. The code of this program is the genome, but this program needs the entire cell as well as the cell’s environment to run properly.
Artificial Intelligence-Based Image Classification Techniques for Hydrologic Applications
Published in Applied Artificial Intelligence, 2022
In GEP, the process commences random selection of an initial population having peculiar characteristics of the class. This initial population sample helps to generate many pairs of genotype and phenotype comprising an individual chromosome of fixed length for each pair. For potentially practical solutions from all chromosomes, the selection is made based on the fitness value using a fitness proportionate selection operation, generally known as the roulette wheel selection process. Genetic operators replicate the selected chromosome to apply modification, replication, recombination, and transposition to the genomes of the chromosome. This process helps to add the adaptive and evolution nature to the programming. New chromosomes are then brought down to the previous process of selection and modification. The process continues until the required accuracy, and a maximum number of iterations (generations) are achieved (Ferreira 2001, 2002, 2006). The GEP had performed well in predicting bridge pier scour depth compared to regression and ANN models (Mohammadpour 2017). The GEP has a unique approach for selecting and providing compact, explicit solutions by opting for the most optimized solution from all different types of suitable solutions. Hence, this feature supports its suitability, especially for using GEP in getting mathematical expression for computing bridge scours over other AI programming such as ANN (Khan, Azamathulla, and Tufail 2012).
Numerical modeling of DNA nucleotides binding process mechanics considering oscillations
Published in Mechanics of Advanced Materials and Structures, 2022
The nucleotide is an important part of human aging research. A single nucleotide polymorphism (SNP, rs189037) in the promoter region of ATM gene was identified, and significant association between CT genotype and longevity was observed by Chen et al. [1]. Single-nucleotide polymorphisms in DNA repair genes relation to longevity were observed by Cho and Suh [2]. Jobson et al. [3] mentioned possible link between changes in amino acid composition shifts and adaptive evolution of mitochondrial proteomes, providing a longer lifespan. Noma [4] mentioned, that expression regulation of genetic information, and regulation of cell proliferation and apoptosis, are linked as an extension of nucleotide and nucleoside metabolism. Nucleotide dynamics studies are becoming increasingly important. Cyclic nucleotide dynamics in neurons were analyzed by Gorshkov and Zhang [5].
Are KIF6 and APOE polymorphisms associated with power and endurance athletes?
Published in European Journal of Sport Science, 2021
Bartosz Wojciechowicz, M.-J. Nancy Laguette, Marek Sawczuk, Kinga Humińska-Lisowska, Agnieszka Maciejewska-Skrendo, Krzysztof Ficek, Monika Michałowska-Sawczyn, Agata Leońska-Duniec, Mariusz Kaczmarczyk, Jakub Chycki, Grzegorz Trybek, Alison V. September, Paweł Cięszczyk
Power analysis was performed using QUANTO v1.2.4 (http://hydra.usc.edu/gxe). Minor allele frequencies (EUR population) were taken from the 1000 Genomes Project. Statistical analyses were conducted using SNPassoc package for R (version 3.4.0, The R Foundation for Statistical Computing, https://cran.t-project.org) and Statistica (Dell Inc. (2016), version 13). Several genetic models were examined to determine the possible mode of inheritance if a genetic effect was evident on the phenotype at the initial analysis. Namely, if A is an allele associated positively or negatively with the performance status, following a dominant model would imply that the interaction is between the “AA + AB” genotypes versus the “BB” genotype. The recessive model would test an effect mediated by the AA genotype versus “AB + BB” genotypes, whilst the additive model would depict an effect of the AA versus AB versus BB genotypes. Allele frequencies were calculated from genotype counts. Pairwise interactions were determined assuming a codominant genotype model (alleles are concomitantly expressed in the heterozygotes) and codominant x dominant model (one allele can mask another allele’s effect). The p value for the interaction was computed using log-likelihood ratio test with two likelihoods, under (1) an additive SNP model and (2) a full model including SNP-SNP interaction using a general linear model (GLM) framework. Genotype models were constructed with respect to the minor alleles. P values < 0.05 were considered statistically significant.