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 937 records · Page 52Linked to original sources
PubMed2001

A polymorphic effect of sexually differential production costs when one parent controls the sex ratio.

R. A. Fisher's sex ratio theory predicts that if sons and daughters cost fixed amounts of resources to raise and parents have fixed amounts to invest, then the numerical sex ratio of a panmictic population will evolve to be inversely proportional to relative cost. However, the theory assumes control by both parents. We show that allowing one parent to control the sex ratio biases it further from parity than Fisher's theory predicts. Quantitatively, the additional bias towards the cheaper sex depends only very weakly on which sex is in control. Qualitatively, however, the effect is very strong: a monomorphic, mixed-brood strategy evolves only if the more expensive sex is in control. If the controlling sex is cheaper to raise, then the sex ratio is instead achieved through a polymorphism of single-sex broods. Such polymorphisms are seldom observed in nature, generating the prediction that wherever the sexes are not equally costly, sex ratio is usually either under biparental control or under uniparental control by the more expensive sex. However, such polymorphisms do occur, and some of them may be explained by our model.

Animals↗
PubMed2005

Maximum likelihood Jukes-Cantor triplets: analytic solutions.

Maximum likelihood (ML) is a popular method for inferring a phylogenetic tree of the evolutionary relationship of a set of taxa, from observed homologous aligned genetic sequences of the taxa. Generally, the computation of the ML tree is based on numerical methods, which in a few cases, are known to converge to a local maximum on a tree, which is suboptimal. The extent of this problem is unknown, one approach is to attempt to derive algebraic equations for the likelihood equation and find the maximum points analytically. This approach has so far only been successful in the very simplest cases, of three or four taxa under the Neyman model of evolution of two-state characters. In this paper we extend this approach, for the first time, to four-state characters, the Jukes-Cantor model under a molecular clock, on a tree T on three taxa, a rooted triple. We employ spectral methods (Hadamard conjugation) to express the likelihood function parameterized by the path-length spectrum. Taking partial derivatives, we derive a set of polynomial equations whose simultaneous solution contains all critical points of the likelihood function. Using tools of algebraic geometry (the resultant of two polynomials) in the computer algebra packages (Maple), we are able to find all turning points analytically. We then employ this method on real sequence data and obtain realistic results on the primate-rodents divergence time.

Biological Evolution↗
PubMed1996

Population evolution on a multiplicative single-peak fitness landscape.

A theory for evolution of either gene sequences or molecular sequences must take into account that a population consists of a finite number of individuals with related sequences. Such a population will not behave in the deterministic way expected for an infinite population, nor will it behave as in adaptive walk models, where the whole of the population is represented by a single sequence. Here we study a model for evolution of population in a fitness landscape with a single fitness peak. This landscape is simple enough for finite size population effects to be studied in detail. Each of the N individuals in the population is represented by a sequence of L genes which may either be advantageous or disadvantageous. The fitness of an individual with k disadvantageous genes is Wk = (1-s)k, where s determines the strength of selection. In the limit L-->infinity, the model reduces to the problem of Muller's Ratchet: the population moves away from the fitness peak at a constant rate due to the accumulation of disadvantageous mutations. For finite length sequences, a population placed initially at the fitness peak will evolve away from the peak until a balance is reached between mutation and selection. From then on the population will wander through a spherical shell in sequence space at a constant mean Hamming distance from the optimum sequence. We give an approximate theory for the way depends on N, L, s, and the mutation rate u. This is found to agree well with numerical simulation. Selection is less effective on small populations, so increases as N decreases. Our simulations also show that the mean overlap between gene sequences separated by a time of t generations is of the form Q(t) = Q infinity + (Q0-Q infinity)exp(-2ut), which means that the rate of evolution within the spherical shell is independent of the selection strength. We give a simplified model which can be solved exactly for which Q(t) has precisely this form. We then consider the limit L-->infinity keeping U = uL constant. We suppose that each mutation may be favourable with probability p, or unfavourable with probability 1-p. We show that for p less than a critical value pc, the population decreases in fitness for all values of U, whereas for pc < p < 1/2, the population increases in fitness for small U and decreases in fitness for large U. In this case there is an optimum non-zero value of U at which the fitness increases most rapidly, and natural selection will favour species with non-zero mutation rates.

Animals↗
PubMed2002

Estimating absolute rates of molecular evolution and divergence times: a penalized likelihood approach.

Rates of molecular evolution vary widely between lineages, but quantification of how rates change has proven difficult. Recently proposed estimation procedures have mainly adopted highly parametric approaches that model rate evolution explicitly. In this study, a semiparametric smoothing method is developed using penalized likelihood. A saturated model in which every lineage has a separate rate is combined with a roughness penalty that discourages rates from varying too much across a phylogeny. A data-driven cross-validation criterion is then used to determine an optimal level of smoothing. This criterion is based on an estimate of the average prediction error associated with pruning lineages from the tree. The methods are applied to three data sets of six genes across a sample of land plants. Optimally smoothed estimates of absolute rates entailed 2- to 10-fold variation across lineages.

Algorithms↗
PubMed1999

Search for the mechanism of genetic variation in the pro gene of human immunodeficiency virus.

To study the mechanism of evolution of the human immunodeficiency virus (HIV) protease gene (pro), we analyzed a database of 213 pro sequences isolated from 11 HIV type 1-infected patients who had not been treated with protease inhibitors. Variation in pro is restricted to rare variable bases which are highly diverse and differ in location among individuals; an average variable base appears in about 16% of individuals. The average intrapatient distance per individual variable site, 27%, is similar for synonymous and nonsynonymous sites, although synonymous sites are twice as abundant. The latter observation excludes selection for diversity as an important, permanently acting factor in the evolution of pro and leaves purifying selection as the only kind of selection. Based on this, we developed a model of evolution, both within individuals and along the transmission chain, which explains variable sites as slightly deleterious mutants slowly reverting to the better-fit variant during individual infection. In the case of a single-source transmission, genetic bottlenecks at the moment of transmission effectively suppress selection, allowing mutants to accumulate along the transmission chain to high levels. However, even very rare coinfections from independent sources are, as we show, able to counteract the bottleneck effect. Therefore, there are two possible explanations for the high mutant frequency. First, the frequency of coinfection in the natural host population may be quite low. Alternatively, a strong variation of the best-adapted sequence between individuals could be caused by a combination of an immune response present in early infection and coselection.

Base Sequence↗
PubMed2006

Automated phylogenetic detection of recombination using a genetic algorithm.

The evolution of homologous sequences affected by recombination or gene conversion cannot be adequately explained by a single phylogenetic tree. Many tree-based methods for sequence analysis, for example, those used for detecting sites evolving nonneutrally, have been shown to fail if such phylogenetic incongruity is ignored. However, it may be possible to propose several phylogenies that can correctly model the evolution of nonrecombinant fragments. We propose a model-based framework that uses a genetic algorithm to search a multiple-sequence alignment for putative recombination break points, quantifies the level of support for their locations, and identifies sequences or clades involved in putative recombination events. The software implementation can be run quickly and efficiently in a distributed computing environment, and various components of the methods can be chosen for computational expediency or statistical rigor. We evaluate the performance of the new method on simulated alignments and on an array of published benchmark data sets. Finally, we demonstrate that prescreening alignments with our method allows one to analyze recombinant sequences for positive selection.

Algorithms↗
PubMed2006

Measurement and modeling of the surface potential evolution of hydrated cement pastes as a function of degradation.

Hydrated cement pastes (HCP) have a high affinity with a lot of (radio)toxic products and can be used as waste confining materials. In cementitious media, elements are removed from solution via (co)precipitation reactions or via sorption/diffusion mechanisms as surface complexation equilibria. In this study, to improve the knowledge of the surface charge evolution vs the degradation of the HCP particles, two cements have been studied: CEM-I (ordinary Portland cement, OPC) and CEM-V (blast furnace slag and fly ash added to OPC). Zeta potential measurements showed that two isoelectric points exist vs HCP leaching, i.e., pH. Zeta potential increases from -17 to +20 mV for pH 13.3 to pH 12.65 (fresh HCP states) and decreases from 20 to -8 mV for pH 12.65 to 11 (degraded HCP states). The use of a simple surface complexation model of C-S-H, limited in comparison with the structural modeling of C-S-H in literature, allows a good prediction of the surface potential evolution of both HCP. Using this operational modeling, the surface charge is controlled by the deprotonation of surface sites (>SO(-)) and by the sorption of calcium (>SOCa(+)), which brings in addition a positive charge. The calcium concentration is controlled by portlandite or calcium silicate hydrate (C-S-H) solubilities.

Journal Article↗
PubMed2002

A gene network model accounting for development and evolution of mammalian teeth.

Generation of morphological diversity remains a challenge for evolutionary biologists because it is unclear how an ultimately finite number of genes involved in initial pattern formation integrates with morphogenesis. Ideally, models used to search for the simplest developmental principles on how genes produce form should account for both developmental process and evolutionary change. Here we present a model reproducing the morphology of mammalian teeth by integrating experimental data on gene interactions and growth into a morphodynamic mechanism in which developing morphology has a causal role in patterning. The model predicts the course of tooth-shape development in different mammalian species and also reproduces key transitions in evolution. Furthermore, we reproduce the known expression patterns of several genes involved in tooth development and their dynamics over developmental time. Large morphological effects frequently can be achieved by small changes, according to this model, and similar morphologies can be produced by different changes. This finding may be consistent with why predicting the morphological outcomes of molecular experiments is challenging. Nevertheless, models incorporating morphology and gene activity show promise for linking genotypes to phenotypes.

Animals↗
PubMed2006

CAFE: a computational tool for the study of gene family evolution.

SUMMARY: We present CAFE (Computational Analysis of gene Family Evolution), a tool for the statistical analysis of the evolution of the size of gene families. It uses a stochastic birth and death process to model the evolution of gene family sizes over a phylogeny. For a specified phylogenetic tree, and given the gene family sizes in the extant species, CAFE can estimate the global birth and death rate of gene families, infer the most likely gene family size at all internal nodes, identify gene families that have accelerated rates of gain and loss (quantified by a p-value) and identify which branches cause the p-value to be small for significant families. AVAILABILITY: Software is available from http://www.bio.indiana.edu/~hahnlab/Software.html

Algorithms↗
PubMed2002

Reconstructing the duplication history of tandemly repeated genes.

We present a novel approach to deal with the problem of reconstructing the duplication history of tandemly repeated genes that are supposed to have arisen from unequal recombination. We first describe the mathematical model of evolution by tandem duplication and introduce duplication histories and duplication trees. We then provide a simple recursive algorithm which determines whether or not a given rooted phylogeny can be a duplication history and another algorithm that simulates the unequal recombination process and searches for the best duplication trees according to the maximum parsimony criterion. We use real data sets of human immunoglobulins and T-cell receptors to validate our methods and algorithms. Identity between most parsimonious duplication trees and most parsimonious phylogenies for the same data, combined with the agreement with additional knowledge about the sequences, such as the presence of polymorphisms, shows strong evidence that our reconstruction procedure provides good insights into the duplication histories of these loci.

Algorithms↗
PubMedDate not supplied

[Computer-assisted model of weight gain during pregnancy].

The goal of this study was to modelize the evolution of "ideal" weight gain during pregnancy and to generate automatically the appropriate diet. This computerized model has been developed on a microcomputer and has two units: the first unit calculates the "ideal" weight gain during pregnancy, based on the curves of Rosso which show that weight gain is not linear with term and depends of the prepregnancy weight. The second unit calculates the appropriate diet which is depending for the first visit on height, prepregnancy weight and weight gain and for the followed visits on weight gain and the diet situation of the previous visit. The next step will be the medical evaluation of this computer-aided modelization of weight gain during pregnancy.

Computer Simulation↗
PubMed2006

Evolutionary product unit based neural networks for regression.

This paper presents a new method for regression based on the evolution of a type of feed-forward neural networks whose basis function units are products of the inputs raised to real number power. These nodes are usually called product units. The main advantage of product units is their capacity for implementing higher order functions. Nevertheless, the training of product unit based networks poses several problems, since local learning algorithms are not suitable for these networks due to the existence of many local minima on the error surface. Moreover, it is unclear how to establish the structure of the network since, hitherto, all learning methods described in the literature deal only with parameter adjustment. In this paper, we propose a model of evolution of product unit based networks to overcome these difficulties. The proposed model evolves both the weights and the structure of these networks by means of an evolutionary programming algorithm. The performance of the model is evaluated in five widely used benchmark functions and a hard real-world problem of microbial growth modeling. Our evolutionary model is compared to a multistart technique combined with a Levenberg-Marquardt algorithm and shows better overall performance in the benchmark functions as well as the real-world problem.

Algorithms↗
PubMed2000

Language evolution and information theory.

This paper places models of language evolution within the framework of information theory. We study how signals become associated with meaning. If there is a probability of mistaking signals for each other, then evolution leads to an error limit: increasing the number of signals does not increase the fitness of a language beyond a certain limit. This error limit can be overcome by word formation: a linear increase of the word length leads to an exponential increase of the maximum fitness. We develop a general model of word formation and demonstrate the connection between the error limit and Shannon's noisy coding theorem.

Biological Evolution↗
PubMed1991

Models of the human brain and the surrounding media: their influence on the reliability of source localization.

This article is a review of the evolution of models of the head as used in dipole source localization. Models fall into two classes: those that can be expressed in simple analytic form, such as the homogeneous sphere or spherical three-shell models, or those that can only be solved by numerical methods, such as the finite element approach. The latter models always involve heavy procedural and computational burdens. The trend over the last decade has been to use these more advanced models to estimate the error that would be incurred if one of the simpler spherical models were used instead for dipole source localization. An estimate is presented of the magnitudes of the random and systematic errors of localization that may be expected when using these methods.

Brain↗
PubMed1994

A model of DNA aneuploidization and evolution in colorectal cancer.

BACKGROUND: Extensive chromosome and DNA content heterogeneity within and between human solid tumors has been observed using both classical karyotype and DNA cytometry. Experimental evidence suggests, at least in some tumor types, that DNA stemline heterogeneity in tumor progression is according to a three-compartment model with diploidy shifting to tetraploidy and then to hypotetraploidy. EXPERIMENTAL DESIGN: The human colorectal adenoma-carcinoma sequence appears as one of the most potentially informative systems for the study of DNA stemline heterogeneity in human tumors since adenomas, adenomas with early cancer, and adenocarcinomas in nontreated patients represent clear morphologically distinct stages of tumor progression. The quantitative measurement of DNA content in the G0.1 phase of the cell cycle was performed by high resolution flow cytometry in a large number of cases using multiple fresh or frozen samples. RESULTS: The distribution of the degree of DNA aneuploidy values, also known as DNA index, (DI not equal to 1) among 467 human precancer and cancer colorectal lesions was clearly nonrandom and showed modes at DI = 0.9, 1.2, 1.5, 1.8, and 2.2 with a clear valley at DI = 1.3. Whereas DNA aneuploid subclones within early lesions were up to about 80% near-diploid (DI < or = 1.3), DNA subclones within advanced cancer were in the vast majority with DI = 1.5-1.8 and, in a small fraction, with DI > 2. In addition, in adenomas with early cancer, which represent a link in colorectal tumor progression, early and late DNA stemlines often coexisted. CONCLUSIONS: The natural history of the colorectal adenoma-carcinoma sequence appears to be characterized by near-diploid subclones as early events and by late-stage hypotetraploidy. A new model is proposed that predicts the origin of the near-diploid subclones by "loss of symmetry" in cell division and their evolution (in particular hypodiploid) to the late-stage hypotetraploidy by tetraploidization. This model agrees with recent data associating molecular biology events, cytogenetic data, and DNA stemline heterogeneity in colorectal and other tumor systems.

Adenocarcinoma↗
PubMed2006

Real-time sea-level gauge observations and operational oceanography.

The contribution of tide-gauge data, which provide a unique monitoring of sea-level variability along the coasts of the world ocean, to operational oceanography is discussed in this paper. Two distinct applications that both demonstrate tide-gauge data utility when delivered in real-time are illustrated. The first case details basin-scale operational model validation of the French Mercator operational system applied to the North Atlantic. The accuracy of model outputs in the South Atlantic Bight both at coastal and offshore locations is evaluated using tide-gauge observations. These data enable one to assess the model's nowcasts and forecasts reliability which is needed in order for the model boundary conditions to be delivered to other coastal prediction systems. Such real-time validation is possible as long as data are delivered within a delay of a week. In the second application, tide-gauge data are assimilated in a storm surge model of the North Sea and used to control model trajectories in real-time. Using an advanced assimilation scheme that takes into account the swift evolution of model error statistics, these observations are shown to be very efficient to control model error, provided that they can be assimilated very frequently (i.e. available within a few hours).

Computer Systems↗
PubMed1989

Comparative methods for examining adaptation depend on evolutionary models.

Comparisons among taxa provide a powerful means for helping to understand why primate species differ from each other in morphology, behaviour and life history. Comparative tests can also mislead when not applied correctly, and correct application means taking into account the phylogenetic relationships among the species being compared. Adaptation is defined as a comparative concept. The reasons for phenotypic similarity among closely related taxa are summarized. Different models of evolutionary change dictate different methods for reconstructing ancestral character states and for performing comparative analyses on categorical and continuously varying character. All comparative methods rely either implicitly of explicitly on some model of how evolution proceeds. The choice of a particular method of analysis is, therefore, an implicit choice of a model of evolution.

Adaptation, Biological↗