PubMed Health⌕ Search

SEARCH · PubMed Health

Results for “Models of evolution”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9Linked to original sources
PubMed1984

Genetic and strategic models for the evolution of mating systems.

Male and female fitnesses in the Shaw-Mohler equation are partitioned into components which putatively determine mating systems. The resultant genetic models provide criteria for evolutionary stable population states and yield strategic models based on maximization principles and fitness sets.

Alleles↗
PubMed1988

A domain model for eukaryotic DNA organization: a molecular basis for cell differentiation and chromosome evolution.

A model for eukaryotic chromatin organization is presented in which the basic structural and functional unit is the DNA domain. This simple model predicts that both chromosome replication and cell type-specific control of gene expression depend on a combination of stable and dynamic DNA-nuclear matrix interactions. The model suggests that in eukaryotes, DNA regulatory processes are controlled mainly by the intranuclear compartmentalization of the specific DNA sequences, and that control of gene expression involves multiple steps of specific DNA-nuclear matrix interactions. Predictions of the model are tested using available biochemical, molecular and cell biological data. In addition, the domain model is discussed as a simple molecular mechanism to explain cell differentiation in multi-cellular organisms and to explain the evolution of eukaryotic genomes consisting mainly of repetitive sequences and "junk" DNA.

Animals↗
PubMed1982

A mathematical model of biological evolution.

In order to understand generally how the biological evolution rate depends on relevant parameters such as mutation rate, intensity of selection pressure and its persistence time, the following mathematical model is proposed: dNn(t)/dt = (mn(t) - mu)Nn(t) + muNn-1(t) (n = 0,1,2,3,...), where Nn(t) and mn(t) are respectively the number and Malthusian parameter of replicons with step number n in a population at time t and mean is the mutation rate, assumed to be a positive constant. The step number of each replicon is defined as either equal to or larger by one than that of its parent, the latter case occurring when and only when mutation has taken place. The average evolution rate defined by v infinity identical to lim t leads to infinity sigma infinity n = o nNn(t)/t sigma infinity n = o Nn(t) is rigorously obtained for the case (i) mn(t) = mn is independent of t (constant fitness model), where mn is essentially periodic with respect to n, and for the case (ii) mn(t) = s(-1) n+[t/tau] (periodic fitness model), together with the long time average -m infinity of the average Malthusian parameter -m identical to sigma infinity n = o mn(t)Nn(t)/sigma infinity n = o Nn(t). The biological meaning of the results is discussed, comparing them with the features of actual molecular evolution and with some results of computer simulation of the model for finite populations.

Animals↗
PubMed1997

Non random DNA evolution.

A model for testing random molecular evolution is proposed. Randomness of recurrent mutation is defined based on isotropy and zero covariance among nucleotide sites. Assuming an equal rate of mutation for the bases A, T, G, and C, in both DNA strands, a mutational matrix of transformation A, T, G, and C with 6 parameters is developed. Under this model the equilibrium proportions (F) of the bases are FA = FT = (D + E)/[2(D + E + H + J)] and FG = FC = (H + J)/[2(D + E + H + J)], D, E, H, J being 4 of the 6 matrix parameters. Thus the expected (FA + FT)/(FG + FC) ratio can also be tested. If the average rate of mutation is 10(-8) per nucleotide site and cell replication, the equilibrium for every site, in most species, is reached in 10(8) years. Eight DNA segments from human, bacteria, fungus and insect genomes were chosen to test these proportions and their heterogeneity among coding and non coding subsegments. While FG was similar to FC as expected, FA was highly different from FT Huge heterogeneities were found between coding and non coding segments and among non coding segments. These results are a strong evidence for non randomness of molecular evolution.

Animals↗
PubMedDate not supplied

[Tandem DNA repeats in the vertebrate genome: structure, possible mechanisms of formation and evolution].

Possible models for the generation and the evolution of tandem repeats are discussed. The model of A.J. Jeffreys and co-workers as well as facts, supporting or contradicting this model are discussed. Facts supporting the hypothesis of the generation of the tandem repeats as the result of mitotic recombination are described. On the basis of an analysis of the structure of the tandem repeats containing loci, it is supposed that there exist space and time relations between the multimerization of the tandem repeats and tandem gene duplication. On the basis of this supposition, the generation of majority of the tandem repeated gene as a result of sister chromatids recombination in mitosis is proposed. Factors determining the existence of recombination hotspots of are discussed. Some specific features of the evolution of tandem repeats of the coding region are also described.

Animals↗
PubMed1986

[Mathematical model for an evolutive and hierarchical living system, based on the theory of categories].

The notion of an evolutive hierarchical system proposed here retains the following characteristics of some natural systems, like living organisms: they have an internal organization consisting of more or less complex components with interrelations; they maintain their organization in time although their components are changing; they may be studied at several complexity levels (e.g., molecular, cellular, ...). The idea is to model the state of the system at a given instant by a category, the state transition by a functor, a complex object by the (direct) limit of a pattern of linked objects (its own organization). The emergence of new properties for a complex object is measured, and a development process is described.

Animals↗
PubMed1997

Genetic definition of a protein-splicing domain: functional mini-inteins support structure predictions and a model for intein evolution.

Inteins are protein-splicing elements, most of which contain conserved sequence blocks that define a family of homing endonucleases. Like group I introns that encode such endonucleases, inteins are mobile genetic elements. Recent crystallography and computer modeling studies suggest that inteins consist of two structural domains that correspond to the endonuclease and the protein-splicing elements. To determine whether the bipartite structure of inteins is mirrored by the functional independence of the protein-splicing domain, the entire endonuclease component was deleted from the Mycobacterium tuberculosis recA intein. Guided by computer modeling studies, and taking advantage of genetic systems designed to monitor intein function, the 440-aa Mtu recA intein was reduced to a functional mini-intein of 137 aa. The accuracy of splicing of several mini-inteins was verified. This work not only substantiates structure predictions for intein function but also supports the hypothesis that, like group I introns, mobile inteins arose by an endonuclease gene invading a sequence encoding a small, functional splicing element.

Amino Acid Sequence↗
PubMed1975

General kin selection models for genetic evolution of sib altruism in diploid and haplodiploid species.

A population genetic approach is presented for general analysis and comparison of kin selection models of sib and half-sib altruism. Nine models are described, each assuming a particular mode of inheritance, number of female inseminations, and Mendelian dominance of the altruist gene. In each model, the selective effects of altruism are described in terms of two general fitness functions, A(beta) and S(beta), giving respectively the expected fitness of an altruist and a nonaltruist as a function of the fraction of altruists beta in a given sibship. For each model, exact conditions are reported for stability at altruist and nonaltruist fixation. Under the Table 3 axions, the stability conditions may then be partially ordered on the basis of implications holding between pairs of conditions. The partial orderings are compared with predictions of the kin selection theory of Hamilton.

Biological Evolution↗
PubMed1989

The domain model for eukaryotic DNA organization. 2: A molecular basis for constraints on development and evolution.

A model for eukaryotic DNA organization has been proposed in which DNA regulatory processes depend on multiple site-specific DNA-nuclear matrix interactions throughout a DNA domain. In this model gene regulation depends on combinations of a few control factors in a cell to activate cell type-specific genes. This model suggests simple molecular mechanisms for organismal development which can account for sequential activation of appropriate groups of genes throughout development and for specific constraints on developmental pathways. Additionally, these suggested developmental pathways are consistent with mechanisms of evolution in which gradualism and punctuated equilibrium are not exclusive of one another and are interrelated mechanisms of evolution that are both induced by specific chromosomal mutations.

Animals↗
PubMed1998

Models of molecular evolution and phylogeny.

Phylogenetic reconstruction is a fast-growing field that is enriched by different statistical approaches and by findings and applications in a broad range of biological areas. Fundamental to these are the mathematical models used to describe the patterns of DNA base substitution and amino acid replacement. These may become some of the basic models for comparative genome research. We discuss these models, including the analysis of observed DNA base and amino acid mutation patterns, the concept of site heterogeneity, and the incorporation of structural biology data, all of which have become particularly important in recent years. We also describe the use of such models in phylogenetic reconstruction and statistical methods for the comparison of different models.

Amino Acid Substitution↗
PubMed1987

Animal models for the evolution of thrombotic disease.

Naturally occurring hemorrhagic and thrombotic diseases of animals closely parallel their human counterparts. While such models may be particularly useful in studying the pathogenesis of human disease, it is usually more realistic to depend upon experimentally induced disease models. The species selected for use is therefore of major importance in providing meaningful extrapolation to humans, as are the experimental design and type of procedure (in vitro, ex vivo, in vivo). Regardless of the test system used when in vitro procedures are employed, these must be translated eventually to the in vivo situation. Information about the normal aging process of different species is important here and should influence selection of the species and test system. The ideal situation may not be feasible or pertain because of cost, availability, size, and investigator familiarity, or lack thereof, with the most suitable species or model.

Animals↗
PubMed1995

Human and rodent DNA sequence comparisons: a mosaic model of genomic evolution.

Three patterns of DNA sequence conservation have been identified from five human and rodent genomic sequence comparisons. First, a divergent pattern was observed in the noncoding sequences of the beta-globin and gamma-crystallin gene clusters, and second, a highly conserved pattern was observed in the noncoding regions of the T cell receptor C alpha-C delta, and the alpha- and beta-myosin-heavy-chain genes. A third, mixed pattern has also been found in the immunoglobulin IgH C mu-C delta gene region. These three patterns of genomic evolution pose the fascinating possibility that large portions of the genome evolve at different rates.

Animals↗