Biomedical subjects

C R Stephens

Publications and source records attributed to C R Stephens.

10 recordsLinked to original sources

PubMed1999

Codon bias and mutability in HIV sequences.

A survey of the patterns of synonymous codon preference in the HIV env gene reveals a correlation between the codon bias and the mutability requirements of different regions of the protein. At hypervariable regions in gp120 one finds a greater proportion of codons that tend to mutate nonsynonymously, but to a target that is similar in hydrophobicity and volume. We argue that this strategy results from a compromise between the selective pressure placed on the virus by the induced immune response, which favors amino acid substitutions in the complementarity determining regions, and the negative selection against missense mutations that violate structural constraints of the env protein.

Codon↗

PubMed1999

Symmetry breaking and adaptation: evidence from a 'toy model' of a virus.

We argue that an induced breaking of the genetic synonym symmetry due to the action of genetic operators such as mutation can enhance the adaptability of a species to changes in the environment. In the case of a virus, the claim is that the codon bias in the neutralization epitope improves the virus' ability to generate mutants that evade the induced immune response. We support our claim with a simple 'toy model' of a viral epitope evolving in competition with the immune system. The effective selective advantage of a higher mutability leads to a dominance of codons that favor non-synonymous mutations. As further evidence we present a simple model for a genetic regulatory network that leads to adaptive evolution in a population of giraffes by means of an induced symmetry breaking rather than through any direct selective advantage.

Adaptation, Physiological↗

PubMed1998

Emergence of algorithmic language in genetic systems.

In genetic systems there is a non-trivial interface between the sequence of symbols which constitutes the chromosome, or 'genotype', and the products which this sequence encodes--the 'phenotype'. This interface can be thought of as a 'computer'. In this case the chromosome is viewed as an algorithm and the phenotype as the result of the computation. In general, only a small fraction of all possible sequences of symbols makes any sense for a given computer. The difficulty of finding meaningful algorithms by random mutation is known as the brittleness problem. In this paper we show that mutation and crossover favor the emergence of an algorithmic language which facilitates the production of meaningful sequences following random mutations of the genotype. We base our conclusions on an analysis of the population dynamics of a variant of Kitano's neurogenetic model wherein the chromosome encodes the rules for cellular division and the phenotype is a 16-cell organism interpreted as a connectivity matrix for a feed-forward neural network. We show that an algorithmic language emerges, describe this language in extenso, and show how it helps to solve the brittleness problem.

Algorithms↗

PubMed1998

Self-adaptation in evolving systems.

A theoretical and experimental analysis is made of the effects of self-adaptation in a simple evolving system. Specifically, we consider the effects of coding the mutation and crossover probabilities of a genetic algorithm evolving in certain model fitness landscapes. The resultant genotype-phenotype mapping is degenerate in fitness space, there being no direct selective advantage for one probability versus another. Thus there is a "symmetry" between various genotypes that all correspond to the same phenotype. We show that the action of mutation and crossover lifts this degeneracy, that is, the genetic operators induce a breaking of the genotype-phenotype symmetry, thus leading to a preference for those genotypes that propagate most successfully into future generations. We demonstrate that this induced symmetry breaking allows the system to self-adapt in a time-dependent environment.

Adaptation, Physiological↗

PubMed1988

Diabetes in pregnancy: maternal and infant outcome.

Previous studies have shown that diabetic women more commonly have complications of pregnancy and adverse infant outcomes than do other women. However, most of the studies have not evaluated women with gestational diabetes separately. The purpose of this study was to evaluate pregnancy complications and infant morbidity and mortality among births to women with gestational diabetes and women with established diabetes. Birth certificate data from 1984 in Washington State linked with death certificate data provided information on complications of pregnancy and infant outcome for 422 gestational diabetics and 144 established diabetics. A comparison group of 856 non-diabetic women who delivered a child was selected at random. Both established and gestational diabetic women were more likely to be reported to develop pre-eclampsia (relative risk (RR) = 4.0 and 9.6). Established and gestational diabetic women were also at increased risk of delivery by Caesarean section (RR = 2.1 and 5.0). Infants of established diabetics had a higher risk of congenital anomalies (RR = 7.6) than infants of non-diabetics and were at increased risk of death in the first 4 weeks (RR = 7.9) and the first year of life (RR = 5.0). Gestational diabetics were more likely to have high birthweight babies (greater than 4000 g) (RR = 2.1) while established diabetics were more likely to have babies at either extreme of birthweight (greater than 4000 g, RR = 1.7; less than 2500 g, RR = 3.2). We conclude that both gestational and established diabetes are associated with important increases in risk of pregnancy complications and adverse infant outcomes.

Adult↗

PubMed1987