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Antithrombin–Heparin Complexes
Published in Severian Dumitriu, Valentin Popa, Polymeric Biomaterials, 2020
Leslie R. Berry, Anthony K.C. Chan
Antithrombin is produced within hepatocytes of the liver in mammalians. The gene for anti-thrombin resides entirely within the long arm of chromosome 1 [32] within a region that extends over an unbroken stretch of ∼19 kb, including seven exons and six introns [33,34]. The open reading frame for human antithrombin contains 1396 nucleotides. At the 5′ end of the reading frame there is a section of 96 nucleotides which code for a 32 amino acid segment called the signal peptide [34]. This N-terminal peptide is removed prior to release from the cell. Within mammalian species, 10% to 15% variation in primary sequence has been reported but high conservation has been observed in the critical reactive site regions [35].
Multi-Objective Optimization Concepts
Published in Yezid Donoso, Ramon Fabregat, Multi-Objective Optimization in Computer Networks Using Metaheuristics, 2016
By means of the roulette method we select, for example, the following chromosomes: Chromosome1→2.5Chromosome2→1.3
Genetic Algorithms for Optimization
Published in Adrian A. Hopgood, Intelligent Systems for Engineers and Scientists, 2021
In an under-specified chromosome, such as [(3, 1) (1, 0)], no value is provided for at least one of the genes, namely gene #2. Chromosome [(1, 1) (3, 0) (1, 0)] is both under-specified and over-specified since it lacks gene #2 but contains multiple occurrences of gene #1. Whether under-specification is problematic depends on the nature of the optimization task. In cases where values must be found for each parameter, under-specified chromosomes must be repaired in some way. The unspecified genes may be set to random values, or to the values used in previously discovered fit chromosomes.
Research on reducing fuzzy test sample set based on heuristic genetic algorithm
Published in Systems Science & Control Engineering, 2021
Zhihua Wang, Manman Cheng, Yongjian Wang
In the 0–1 matrix, one column represents a chromosome, ‘1’ in the matrix means that a certain chromosome contains this gene, and ‘0’ means that this chromosome does not contain this gene. The algorithm uses the priority idea of performance-cost ratio: Performance refers to the number of columns containing ‘1’ in the set corresponding to a gene in the chromosome. The more the number, the more rows covered by the column, indicating the higher performance of the chromosome. Suppose that the set of all chromosomes generated when using a genetic algorithm for a group of chromosomes is: S = {s1, s2, s3, s4, s5}, where s1 = {2, 4, 6} and s2 = {1, 4, 6}, s3 = {2, 3, 5, 6}, s4 = {2, 3, 7}, s5 = {1, 7} (use numbers to directly represent the genes and positions they contain). The following example will be used to illustrate the idea of combining approximation. Set coverage eliminates redundancy
Advances in characterizing microbial community change and resistance upon exposure to lead contamination: Implications for ecological risk assessment
Published in Critical Reviews in Environmental Science and Technology, 2020
S. Elizabeth George, Yongshan Wan
C. metallidurans strain CH34 harbors additional genes that confer Pb resistance. The pbrR2 (Rmet_2302), cadA, pbrC2 operon is located on chromosome 1 in a genomic island (CMGI-1) and may maintain low cellular Pb(II) concentration (Taghavi et al., 2009). The zntA gene (Zn(II) efflux protein), which is induced by Pb(II) (a Staphylococcus aureus CadA (Cd(II) efflux protein homolog in Escherichia coli induced by Zn(II)/Cd(II)/Pb(II) (Beard et al., 1997; Rensing et al., 1998), is a P-Type ATPase located on chromosome 2. The pbrR3 gene (Rmet_3456; pbrR691) which preferentially binds Pb(II), is located on chromosome 1 (Monsieurs et al., 2011; Taghavi et al., 2009). These genes have been shown to rescue mutations in complementary genes in the C. metallidurans strain CH34 primary Pb resistance operon, pbrUTRABCD (Taghavi et al., 2009). Because the prevalence of host Pb resistance genes, which have the potential to bind Pb(II) and interfere with biosensor Pb detection, minimizing their presence should improve detection.
An unexpected world population variation of MCT1 polymorphism 1470T > A involved in lactate transport
Published in European Journal of Sport Science, 2018
Federico Onali, Carla M. Calò, Myosotis Massidda, Miguel M. Álvarez-Álvarez, Maria Esther Esteban
The worldwide variation of MCT1gene (Chromosome 1:113,454,469–113,499,635 reverse strand) and of its polymorphism 1470T > A (SNP rs1049434, Chromosome 1:113456546 forward strand) was analysed with data obtained from the public database 1000 Genomes Phase 3 Browser (Auton et al., 2015). The final data set provided information for 2504 individual genotypes of 26 different populations clustered in 5 super-populations (African, American, East Asia, European and South Asia). With regard to ethical guidelines, the 1000 Genomes Project includes documentation about the Informed Consent signed by all individuals sampled. Compliance with these ethical guidelines is supervised by the 1000 Genomes Project Steering Committee. Allele frequency and heterozygosity (genetic diversity) for each individual population were calculated using the software Genetix (Belkhir, Borsa, Chikhi, Raufaste, & Bonhomme, 1996–2004). Hardy–Weinberg equilibrium, population relationships evaluated through pairwise population differentiation and hierarchical analyses of molecular variation (AMOVA FST) were determined with Arlequin v.3.5 (Excoffier, Laval, & Schneider, 2005). Selection signatures using the gene MCT1 were evaluated through the 1000 Genomes Selection Browser 1.0 (Pybus et al., 2014) comparing data from CEU (European) and YRI (Sub-Saharan), from CEU and CHB (China), from CHB and YRI for FST-rank scores. The browser calculated a rank of probability values that represent the percentile of the statistic for the genetic variant showing the P-value in the genome-level distribution.