scholarly journals Evolutionary dynamics of simple sequence repeats across long evolutionary time scale in genus Drosophila

2012 ◽  
Vol 4 (1) ◽  
pp. 7 ◽  
Author(s):  
Lothar Wissler ◽  
Lars Godmann ◽  
Erich Bornberg-Bauer
Keyword(s):  
Simple Sequence Repeats ◽  
Time Scale ◽  
Evolutionary Dynamics ◽  
Evolutionary Time ◽  
Evolutionary Time Scale ◽  
Simple Sequence

scholarly journals On the evolutionary time scale of the accreting component in massive close binaries: consequences for the supernova event

1981 ◽  
Vol 59 ◽  
pp. 465-468
Author(s):  
C. Doom ◽  
J.P. De Grève
Keyword(s):  
Mass Loss ◽  
Mass Exchange ◽  
Stellar Wind ◽  
Time Scale ◽  
Roche Lobe ◽  
Close Binaries ◽  
Evolutionary Time ◽  
Hydrogen Burning ◽  
Evolutionary Time Scale ◽  
Evolutionary Scenario

AbstractThe remaining core hydrogen burning lifetime after a case B of mass exchange is computed for the mass gaining component in massive close binaries. Effects of stellar wind mass loss and mass loss during Roche Lobe OverFlow (RLOF) are included. Consequences for the evolutionary scenario are discussed.

scholarly journals Are there ergodic limits to evolution? Ergodic exploration of genome space and convergence

2015 ◽  
Vol 5 (6) ◽  
pp. 20150041 ◽  
Author(s):  
Tom C. B. McLeish
Keyword(s):  
Time Scale ◽  
Evolutionary Dynamics ◽  
Compound Eye ◽  
Biological Structure ◽  
Evolutionary Time ◽  
Structural Space ◽  
Interesting Class ◽  
Equivalent Systems ◽  
Genome Space ◽  
Time Required

We examine the analogy between evolutionary dynamics and statistical mechanics to include the fundamental question of ergodicity —the representative exploration of the space of possible states (in the case of evolution this is genome space). Several properties of evolutionary dynamics are identified that allow a generalization of the ergodic dynamics, familiar in dynamical systems theory, to evolution. Two classes of evolved biological structure then arise, differentiated by the qualitative duration of their evolutionary time scales. The first class has an ergodicity time scale (the time required for representative genome exploration) longer than available evolutionary time, and has incompletely explored the genotypic and phenotypic space of its possibilities. This case generates no expectation of convergence to an optimal phenotype or possibility of its prediction. The second, more interesting, class exhibits an evolutionary form of ergodicity—essentially all of the structural space within the constraints of slower evolutionary variables have been sampled; the ergodicity time scale for the system evolution is less than the evolutionary time. In this case, some convergence towards similar optima may be expected for equivalent systems in different species where both possess ergodic evolutionary dynamics. When the fitness maximum is set by physical, rather than co-evolved, constraints, it is additionally possible to make predictions of some properties of the evolved structures and systems. We propose four structures that emerge from evolution within genotypes whose fitness is induced from their phenotypes. Together, these result in an exponential speeding up of evolution, when compared with complete exploration of genomic space. We illustrate a possible case of application and a prediction of convergence together with attaining a physical fitness optimum in the case of invertebrate compound eye resolution.

Effects of extinction on food web structures on an evolutionary time scale

2010 ◽  
Vol 263 (2) ◽  
pp. 161-168 ◽  
Author(s):  
Ryo Hironaga ◽  
Norio Yamamura
Keyword(s):  
Food Web ◽  
Time Scale ◽  
Evolutionary Time ◽  
Evolutionary Time Scale

Preadaptation in Populations of Neural Networks Evolving in a Changing Environment

1995 ◽  
Vol 2 (2) ◽  
pp. 179-197 ◽  
Author(s):  
Henrik Hautop Lund ◽  
Domenico Parisi
Keyword(s):  
Neural Networks ◽  
Time Scale ◽  
Food Preference ◽  
Food Type ◽  
Initial Population ◽  
Evolutionary Time ◽  
Changing Environment ◽  
Evolutionary Time Scale ◽  
New Strategy ◽  
Behavioral Preference

Populations of simple artificial organisms modeled as neural networks evolve a preference for one particular food type in an environment that contains more than one food type if the quantity of energy extracted from each food type is allowed to coevolve with the behavioral preference (evolvable fitness formula). If, after the emergence of the food preference, the preferred food gradually disappears from the environment at the evolutionary time scale, the evolved specialist strategy is maintained until the preferred food type has completely disappeared. Then a new specialist strategy suddenly emerges with a preference for another food type present in the environment. The appearance of the new strategy takes very few generations, in fact much fewer than in a population starting from zero (random initial population) in the same environment. This, together with the fact that the population with an evolutionary past is more efficient than the population starting from zero, suggests that the former population is preadapted to the changed environment. An analysis of the activation values of the hidden units indicates that the new food preference can be an “exaptation,” that is, a new adaptation based on a structure that has previously emerged for adaptively neutral reasons.

The Topology of the Protein Network Influences the Dynamics of Gene Order: From Systems Biology to a Systemic Understanding of Evolution

2008 ◽  
Vol 14 (1) ◽  
pp. 149-156 ◽  
Author(s):  
Carole Knibbe ◽  
Jean-Michel Fayard ◽  
Guillaume Beslon
Keyword(s):  
Systems Biology ◽  
Gene Order ◽  
Time Scale ◽  
Protein Network ◽  
Evolutionary Time ◽  
Mutational Robustness ◽  
Dynamic Interactions ◽  
Term Selection ◽  
Evolutionary Time Scale ◽  
Systemic Understanding

Systems biology invites us to consider the dynamic interactions between the components of a living cell. Here, by evolving artificial organisms whose genomes encode protein networks, we show that a coupling emerges at the evolutionary time scale between the protein network and the structure of the genome. Gene order is more stable when the protein network is more densely connected, which most likely results from a long-term selection for mutational robustness. Understanding evolving organisms thus requires a systemic approach, taking into account the functional interactions between gene products, but also the global relationships between the genome and the proteome at the evolutionary time scale.

scholarly journals Evolutionary Time-Scale of the Begomoviruses: Evidence from Integrated Sequences in the Nicotiana Genome

PLoS ONE ◽  
2011 ◽  
Vol 6 (5) ◽  
pp. e19193 ◽  
Author(s):  
Pierre Lefeuvre ◽  
Gordon W. Harkins ◽  
Jean-Michel Lett ◽  
Rob W. Briddon ◽  
Mark W. Chase ◽  
...  
Keyword(s):  
Time Scale ◽  
Evolutionary Time ◽  
Evolutionary Time Scale

Evolutionary time-scale of primate bocaviruses

2013 ◽  
Vol 14 ◽  
pp. 265-274 ◽  
Author(s):  
Igor V. Babkin ◽  
Alexander I. Tyumentsev ◽  
Artem Yu. Tikunov ◽  
Alexander M. Kurilshikov ◽  
Elena I. Ryabchikova ◽  
...  
Keyword(s):  
Time Scale ◽  
Evolutionary Time ◽  
Evolutionary Time Scale
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