Berlin, Deutschland, 18. Juli 2023 — dnatest.de, eine führende Online-Plattform für den Vergleich von Anbietern von DNA Test, Vaterschaftstest, Herkunftsanalyse und DNA Tests für Hunde, verkündet die strategische Übernahme von Vermögenswerten der nun offline geschalteten Webseite DFG-SPP 1590. Diese Akquisition ist Teil der kontinuierlichen Bemühungen, das Nutzererlebnis auf dnatest.de zu verbessern.
DFG-SPP 1590 war eine bahnbrechende Webseite, die sich in die komplexe Welt der biologischen Evolution vertiefte. Die mittlerweile inaktive Seite konzentrierte sich auf das DFG-Schwerpunktprogramm „Probabilistische Strukturen in der Evolution“ und erforschte stochastische Prozesse in der Populationsgenetik, adaptiver Dynamik und probabilistischen Aspekten der evolutionären Spieltheorie. Mit ihrem umfassenden Inhalt diente sie als wertvolle Ressource für Wissenschaftler und Enthusiasten gleichermaßen, um die komplexen Prozesse und probabilistischen Strukturen der biologischen Evolution zu verstehen.
ENDE DER PRESSEMITTEILUNG
Welcome to the homepage of the DFG SPP Priority Programme 1590
Probabilistic Structures in Evolution
This programme was approved by the Senate of the DFG on April the 19/20th, 2011. It is designed to run for six years. Proposals for the second three-year funding period have been submitted and reviewed on September the 03/04th, 2015. The first funding period ends in December 2015; the second funding period is January 2016 to December 2018.
Aims and scope
The Priority Programme “Probabilistic Structures in Evolution” is devoted to the in-depth theoretical study of stochastic processes in population genetics (that is, describing the evolution of the genetic structure of populations under the action of the various evolutionary forces), stochastic models of adaptive dynamics (that is, individual-based models for the joint description of ecology and evolution), and probabilistic aspects of evolutionary game theory.
Biological evolution is a complex phenomenon driven by various underlying processes, such as mutation and recombination of genetic material, reproduction of individuals, competition, and selection of favourable types. Studying the interplay of these processes requires a substantial use of mathematical models and methods. Over the past decades, much of this modelling and analysis took place on a deterministic level, using dynamical systems and differential equations, and this has led to an elaborate theory. However, the processes of evolution have intrinsically random elements, such as random reproduction, which leads to stochastic fluctuations of gene frequencies and the emergence of random genealogies. The underlying stochastic processes are receiving increased attention, not least because they have shaped present-day genomes. Indeed, the study of these processes is crucial for understanding observations and interpreting data that arise in modern empirical evolutionary biology. From the point of view of mathematics, challenging new structures emerge, such as Fleming-Viot and ancestral processes with high offspring variation, coalescents with spatial and genetic structure, and individual-based models of adaptive dynamics. The main objective of the Priority Programme is the in-depth theoretical study of
- stochastic processes in population genetics (that is, describing the evolution of the genetic structure of populations under the action of the various evolutionary forces, in particular in the presence of selection and recombination),
- stochastic models of adaptive dynamics (that is, individual-based models for the joint description of ecology and evolution), and probabilistic aspects of evolutionary game theory.
Retrospective genealogical aspects are an inherent part of population genetics theory, but should also be developed for game theory and adaptive dynamics. Therefore, random genealogies and trees form a conceptual anchor to all themes in the Priority Programme. In this context, structures such as evolving genealogies, coalescents with highly-variable offspring distribution, and genealogies with genetic and geographic structure will be targeted. The programme thus aims at the further development of the mathematical theory of biological evolution. In addition, projects involving the analysis of related experimental data will be targeted; here, approaches will be model driven rather than purely statistical.