Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Evolutionary”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

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

At least 667 records · Page 37Linked to original sources

InVEST: interactive and visual edge selection tool for constructing evolutionary trees.

InVEST is an interactive and visual tool for constructing evolutionary trees from an ordered list of edges. In this paper it is shown that many methods for constructing evolutionary trees reduce to the edge selection problem. Furthermore, through a simulation study, it is shown that noninteractive methods for edge selection often perform poorly and can conceal alternative solutions. InVEST allows the user to interact with and explore an ordered list of edges facilitating the incorporation of user domain knowledge into the evolutionary tree construction process.

Algorithms↗

A hierarchical method for finding optimal architecture and weights using evolutionary least square based learning.

In this paper, we present a novel approach of implementing a combination methodology to find appropriate neural network architecture and weights using an evolutionary least square based algorithm (GALS).1 This paper focuses on aspects such as the heuristics of updating weights using an evolutionary least square based algorithm, finding the number of hidden neurons for a two layer feed forward neural network, the stopping criterion for the algorithm and finally some comparisons of the results with other existing methods for searching optimal or near optimal solution in the multidimensional complex search space comprising the architecture and the weight variables. We explain how the weight updating algorithm using evolutionary least square based approach can be combined with the growing architecture model to find the optimum number of hidden neurons. We also discuss the issues of finding a probabilistic solution space as a starting point for the least square method and address the problems involving fitness breaking. We apply the proposed approach to XOR problem, 10 bit odd parity problem and many real-world benchmark data sets such as handwriting data set from CEDAR, breast cancer and heart disease data sets from UCI ML repository. The comparative results based on classification accuracy and the time complexity are discussed.

Algorithms↗

Orthologs, paralogs, and evolutionary genomics.

Orthologs and paralogs are two fundamentally different types of homologous genes that evolved, respectively, by vertical descent from a single ancestral gene and by duplication. Orthology and paralogy are key concepts of evolutionary genomics. A clear distinction between orthologs and paralogs is critical for the construction of a robust evolutionary classification of genes and reliable functional annotation of newly sequenced genomes. Genome comparisons show that orthologous relationships with genes from taxonomically distant species can be established for the majority of the genes from each sequenced genome. This review examines in depth the definitions and subtypes of orthologs and paralogs, outlines the principal methodological approaches employed for identification of orthology and paralogy, and considers evolutionary and functional implications of these concepts.

Animals↗

Evolutionary ecology of plant diseases in natural ecosystems.

Plant pathogens cause mortality and reduce fecundity of individual plants, drive host population dynamics, and affect the structure and composition of natural plant communities. Pathogens are responsible for both numerical changes in host populations and evolutionary changes through selection for resistant genotypes. Linking such ecological and evolutionary dynamics has been the focus of a growing body of literature on the effects of plant diseases in natural ecosystems. A guiding principle is the importance of understanding the spatial and temporal scales at which plants and pathogens interact. This review summarizes the effects of diseases on populations of wild plants, focusing in particular on the mediation of plant competition and succession, the maintenance of plant species diversity, as well as the process of rapid evolutionary changes in host-pathogen symbioses.

Adaptation, Physiological↗

Evolutionary psychology: toward a unifying theory and a hybrid science.

Although evolutionary psychology is typically associated with "selfish gene theory," numerous other approaches to the study of mind and behavior provide a wealth of concepts for theorizing about psychology, culture, and development. These include general evolutionary approaches and theories focused on sociality, dual inheritance, multilevel selection, and developmental systems. Most evolutionary accounts use the same methods as Darwin-the "fit among facts"-to use natural selection as an explanation for behavior. Scientific standards for constraining and evaluating such accounts, research into the mutual influence of science and society on the understanding of evolution, and computational technologies for modeling species-typical processes are important considerations. Coevolutionary theories and developmental systems theories may eventually give rise to unification in a broad and general sense. Such a unification would be interdisciplinary and problem centered rather than discipline centered.

Biological Evolution↗

Evolutionary theories of aging: handle with care.

BACKGROUND: Evolutionary theories are considered by a growing number of gerontologists as providing a basis to understand why aging occurs. OBJECTIVE: In such conditions, a risk could exist to favor evolutionary explanations rather than nonevolutionary ones, even when both equally fit the data. METHODS: A paper recently published on longevity in ants is analyzed, and a study of fertility and longevity in human beings is done to illustrate this risk. RESULTS: In the two cases, evolutionary and concurrent hypotheses may apply to the same data. CONCLUSIONS: When both kinds of explanations may be applied, the way to solve the problem is not to favor one explanation by relying on a priori preferences, particularly if the favored hypothesis is still controversial.

Aging↗

Evolutionary theories of aging. 2. The need not to close the debate.

BACKGROUND: Keller and Genoud [Gerontology 1999;45: 336-338] consider that a previous article of Le Bourg [Gerontology 1998;44:345-348] is an inappropriate criticism of evolutionary theories of aging and offer a refutation of this article. OBJECTIVE: We answer that the article was not devoted to the criticism of evolutionary theories of aging but, rather, to the sometimes fast tackling of these theories on what is observed in the wild. Furthermore, we answer to the specific points contained in the Keller and Genoud's article (longevity of ants, reproduction in mammals, and the case of the human species). CONCLUSION: The debate about evolutionary theories of aging is not closed: it would be an error to try to do it before a consensus has been reached.

Aging↗

Liver transplantation-associated de novo hepatitis B virus infection: application of molecular evolutionary analysis.

OBJECTIVE: De novo hepatitis B virus (HBV) infection after liver transplantation has recently been reported to be associated with donors without serum hepatitis B surface antigen (HbsAg) but with hepatitis B core antigen (anti-HBc). We elucidate the source of de novo HBV infection after liver transplantation by molecular evolutionary analysis. METHODS: The serum sample was obtained from a recipient who underwent living related liver transplantation. He was negative for all HBV-related serum markers before the transplantation. The recipient became seropositive for HBsAg at 6 months after transplantation. The liver tissue was obtained from a donor who was seronegative for HBsAg, but positive for anti-HBs and anti-HBc. RESULTS: HBV DNA was detected from the serum and liver tissue in a recipient and donor, respectively. A total of 5 clones each of small-S gene of HBV from the donor and recipient were sequenced. A phylogenetic tree analysis based on small-S gene revealed that all isolates derived from the recipient and donor were clustered together within a close range of evolutionary distances. These results indicated that HBV was transmitted by the liver graft from the donor. CONCLUSIONS: Molecular evolutionary analysis can be adopted for the study of the transmission route of viral infection via organ transplantation.

Adolescent↗

Evolutionary aspects of the genomic organization of rat chromosome 10.

Using FISH and RH mapping a chromosomal map of rat chromosome 10 (RNO10) was constructed. Our mapping data were complemented by other published data and the final map was compared to maps of mouse and human chromosomes. RNO10 contained segments homologous to mouse chromosomes (MMU) 11, 16 and 17, with evolutionary breakpoints between the three segments situated in the proximal part of RNO10. Near one of these breakpoints (between MMU17 and 11) we found evidence for an inversion ancestral to the mouse that was not ancestral to the condition in the rat. Within each of the chromosome segments identified, the gene order appeared to be largely conserved. This conservation was particularly clear in the long MMU11-homologous segment. RNO10 also contained segments homologous to three human chromosomes (HSA5, 16, 17). However, within each segment of conserved synteny were signs of more extensive rearrangements. At least 13 different evolutionary breakpoints were indicated in the rat-human comparison. In contrast to what was found between rat and mouse, the rat-human evolutionary breaks were distributed along the entire length of RNO10.

Animals↗

Comparative mapping of genes flanking the human chromosome 12 evolutionary breakpoint in the pig.

Genes located on human chromosome 12 (HSA12) are conserved on pig chromosomes 5 and 14 (SSC5 and SSC14), with HSA12q23.3-->q24.11 harboring the evolutionary breakpoint between these chromosomes. For this study, pig sequence-tagged sites (STS) were developed for nine HSA12 genes flanking this breakpoint. Radiation hybrid (RH) mapping using the IMpRH panel revealed that COL2A1, DUSP6, KITLG, PAH and STAB2 map to SSC5, while PXN, PLA2G1B, SART3 and TCF1 map to SSC14. Polymorphisms identified in COL2A1, DUSP6, PAH, PLA2G1B and TCF1 were used for genetic linkage mapping and confirmed the map locations for these genes. Our results indicate that the HSA12 evolutionary breakpoint occurs between STAB2 and SART3 in a region spanning less than five million basepairs. These results refine the comparative map of the HSA12 evolutionary breakpoint region and help to further elucidate the extensive gene order rearrangements between HSA12 and SSC5 and 14.

Animals↗

Evolutionary conserved chromosomal segments in the human karyotype are bounded by unstable chromosome bands.

In this paper an ancestral karyotype for primates, defining for the first time the ancestral chromosome morphology and the banding patterns, is proposed, and the ancestral syntenic chromosomal segments are identified in the human karyotype. The chromosomal bands that are boundaries of ancestral segments are identified. We have analyzed from data published in the literature 35 different primate species from 19 genera, using the order Scandentia, as well as other published mammalian species as out-groups, and propose an ancestral chromosome number of 2n = 54 for primates, which includes the following chromosomal forms: 1(a+c(1)), 1(b+c(2)), 2a, 2b, 3/21, 4, 5, 6, 7a, 7b, 8, 9, 10a, 10b, 11, 12a/22a, 12b/22b, 13, 14/15, 16a, 16b, 17, 18, 19a, 19b, 20 and X and Y. From this analysis, we have been able to point out the human chromosome bands more "prone" to breakage during the evolutionary pathways and/or pathology processes. We have observed that 89.09% of the human chromosome bands, which are boundaries for ancestral chromosome segments, contain common fragile sites and/or intrachromosomal telomeric-like sequences. A more in depth analysis of twelve different human chromosomes has allowed us to determine that 62.16% of the chromosomal bands implicated in inversions and 100% involved in fusions/fissions correspond to fragile sites, intrachromosomal telomeric-like sequences and/or bands significantly affected by X irradiation. In addition, 73% of the bands affected in pathological processes are co-localized in bands where fragile sites, intrachromosomal telomeric-like sequences, bands significantly affected by X irradiation and/or evolutionary chromosomal bands have been described. Our data also support the hypothesis that chromosomal breakages detected in pathological processes are not randomly distributed along the chromosomes, but rather concentrate in those important evolutionary chromosome bands which correspond to fragile sites and/or intrachromosomal telomeric-like sequences.

Alouatta↗

Building complex brains--missing pieces in an evolutionary puzzle.

The mechanisms underlying evolution of complex nervous systems are not well understood. In recent years there have been a number of attempts to correlate specific gene families or evolutionary processes with increased brain complexity in the vertebrate lineage. Candidates for evocation of complexity include genes involved in regulating brain size, such as neurotrophic factors or microcephaly-related genes; or wider evolutionary processes, such as accelerated evolution of brain-expressed genes or enhanced RNA splicing or editing events in primates. An inherent weakness of these studies is that they are correlative by nature, and almost exclusively focused on the mammalian and specifically the primate lineage. Another problem with genomic analyses is that it is difficult to identify functionally similar yet non-homologous molecules such as different families of cysteine-rich neurotrophic factors in different phyla. As long as comprehensive experimental studies of these questions are not feasible, additional perspectives for evolutionary and genomic studies will be very helpful. Cephalopod mollusks represent the most complex nervous systems outside the vertebrate lineage, thus we suggest that genome sequencing of different mollusk models will provide useful insights into the evolution of complex brains.

Animals↗

On the use of neural network techniques to analyse sleep EEG data. First communication: application of evolutionary and genetic algorithms to reduce the feature space and to develop classification rules.

To automate sleep stage scoring, the system sleep analysis system to challenge innovative artificial networks (SASCIA) has been developed and implemented. The aims of our investigation were twofold: In addition to automatic sleep stage scoring the hypothesis was tested that the information of only 1 EEG channel (C4-A2) should be sufficient to automatically generate sleep profiles which are comparable with profiles made by sleep experts on the basis of at least 3-channel EEG (C4-A2), EOG and EMG, as EOG and EMG are seen as epiphenomena during sleep and the full information about the sleep stage should--according to our hypothesis--be available in the EEG. The main components of the SASCIA sleep analysis system are designed to meet the requirements of flexible adaptation to the interindividual differences of the sleep EEG. The core of the SASCIA sleep analysis system consists of neural networks. Supervised learning was implemented and the experts' scorings were included into the learning set and test set. The feature selections out of a large number (118) are performed by genetic algorithms and the topologies of the networks are optimized by evolutionary algorithms. Different mathematical procedures were used to evaluate and optimize the efficiency of the system. The profiles generated by SASCIA are in reasonable agreement with the sleep stages scored by experts according to RKR. The development of the system is communicated in three parts: the first communication deals with the application of the neural network techniques using evolutionary and genetic algorithms and with the selection of feature space. The second communication shows the training of these evolutionary optimized network techniques with multiple subjects and the application of context rules, while the third communication shows an improvement in the robustness by the simultaneous application of 9 different networks obtained from 9 subject types which were used in combination with context rules.

Algorithms↗

Variable length representation in evolutionary electronics.

This work investigates the application of variable length representation (VLR) evolutionary algorithms (EAs) in the field of Evolutionary Electronics. We propose a number of VLR methodologies that can cope with the main issues of variable length evolutionary systems. These issues include the search for efficient ways of sampling a genome space with varying dimensionalities, the task of balancing accuracy and parsimony of the solutions, and the manipulation of non-coding segments. We compare the performance of three proposed VLR approaches to sample the genome space: Increasing Length Genotypes, Oscillating Length Genotypes, and Uniformly Distributed Initial Population strategies. The advantages of reusing genetic material to replace non-coding segments are also emphasized in this work. It is shown, through examples in both analog and digital electronics, that the variable length genotype's representation is natural to this particular domain of application. A brief discussion on biological genome evolution is also provided.

Algorithms↗

Efficient and scalable Pareto optimization by evolutionary local selection algorithms.

Local selection is a simple selection scheme in evolutionary computation. Individual fitnesses are accumulated over time and compared to a fixed threshold, rather than to each other, to decide who gets to reproduce. Local selection, coupled with fitness functions stemming from the consumption of finite shared environmental resources, maintains diversity in a way similar to fitness sharing. However, it is more efficient than fitness sharing and lends itself to parallel implementations for distributed tasks. While local selection is not prone to premature convergence, it applies minimal selection pressure to the population. Local selection is, therefore, particularly suited to Pareto optimization or problem classes where diverse solutions must be covered. This paper introduces ELSA, an evolutionary algorithm employing local selection and outlines three experiments in which ELSA is applied to multiobjective problems: a multimodal graph search problem, and two Pareto optimization problems. In all these experiments, ELSA significantly outperforms other well-known evolutionary algorithms. The paper also discusses scalability, parameter dependence, and the potential distributed applications of the algorithm.

Algorithms↗

Comparison of multiobjective evolutionary algorithms: empirical results.

In this paper, we provide a systematic comparison of various evolutionary approaches to multiobjective optimization using six carefully chosen test functions. Each test function involves a particular feature that is known to cause difficulty in the evolutionary optimization process, mainly in converging to the Pareto-optimal front (e.g., multimodality and deception). By investigating these different problem features separately, it is possible to predict the kind of problems to which a certain technique is or is not well suited. However, in contrast to what was suspected beforehand, the experimental results indicate a hierarchy of the algorithms under consideration. Furthermore, the emerging effects are evidence that the suggested test functions provide sufficient complexity to compare multiobjective optimizers. Finally, elitism is shown to be an important factor for improving evolutionary multiobjective search.

Algorithms↗

Design of graph-based evolutionary algorithms: a case study for chemical process networks.

This paper describes the adaptation of evolutionary algorithms (EAs) to the structural optimization of chemical engineering plants, using rigorous process simulation combined with realistic costing procedures to calculate target function values. To represent chemical engineering plants, a network representation with typed vertices and variable structure will be introduced. For this representation, we introduce a technique on how to create problem specific search operators and apply them in stochastic optimization procedures. The applicability of the approach is demonstrated by a reference example. The design of the algorithms will be oriented at the systematic framework of metric-based evolutionary algorithms (MBEAs). MBEAs are a special class of evolutionary algorithms, fulfilling certain guidelines for the design of search operators, whose benefits have been proven in theory and practice. MBEAs rely upon a suitable definition of a metric on the search space. The definition of a metric for the graph representation will be one of the main issues discussed in this paper. Although this article deals with the problem domain of chemical plant optimization, the algorithmic design can be easily transferred to similar network optimization problems. A useful distance measure for variable dimensionality search spaces is suggested.

Algorithms↗

Combining convergence and diversity in evolutionary multiobjective optimization.

Over the past few years, the research on evolutionary algorithms has demonstrated their niche in solving multiobjective optimization problems, where the goal is to find a number of Pareto-optimal solutions in a single simulation run. Many studies have depicted different ways evolutionary algorithms can progress towards the Pareto-optimal set with a widely spread distribution of solutions. However, none of the multiobjective evolutionary algorithms (MOEAs) has a proof of convergence to the true Pareto-optimal solutions with a wide diversity among the solutions. In this paper, we discuss why a number of earlier MOEAs do not have such properties. Based on the concept of epsilon-dominance, new archiving strategies are proposed that overcome this fundamental problem and provably lead to MOEAs that have both the desired convergence and distribution properties. A number of modifications to the baseline algorithm are also suggested. The concept of epsilon-dominance introduced in this paper is practical and should make the proposed algorithms useful to researchers and practitioners alike.

Algorithms↗