Deutsch
 
Hilfe Datenschutzhinweis Impressum
  DetailsucheBrowse

Datensatz

 
 
DownloadE-Mail
  Invasion and effective size of graph-structured populations

Giaimo, S., Arranz, J., & Traulsen, A. (2018). Invasion and effective size of graph-structured populations. PLoS Computational Biology, 14(11): e1006559. doi:10.1371/journal.pcbi.1006559.

Item is

Basisdaten

einblenden: ausblenden:
Genre: Zeitschriftenartikel

Dateien

einblenden: Dateien
ausblenden: Dateien
:
journal.pcbi.1006559.pdf (Verlagsversion), 2MB
Name:
journal.pcbi.1006559.pdf
Beschreibung:
-
OA-Status:
Sichtbarkeit:
Öffentlich
MIME-Typ / Prüfsumme:
application/pdf / [MD5]
Technische Metadaten:
Copyright Datum:
-
Copyright Info:
-

Externe Referenzen

einblenden:
ausblenden:
Beschreibung:
-
OA-Status:

Urheber

einblenden:
ausblenden:
 Urheber:
Giaimo, Stefano1, Autor           
Arranz, Jordi1, Autor           
Traulsen, Arne1, Autor           
Affiliations:
1Department Evolutionary Theory, Max Planck Institute for Evolutionary Biology, Max Planck Society, ou_1445641              

Inhalt

einblenden:
ausblenden:
Schlagwörter: graphs; eigenvectors; evolutionary theory; natural selection; deletion mutation; directed graphs; graph theory; evolutionary genetics
 Zusammenfassung: Author summary Evolving populations, companies, social circles are networks in which genes, resources and ideas circulate. Imagine a useful novelty is introduced in the network: a favorable mutation, a new product concept or a smart idea. Will this novelty be retained and propagated through the network or rather lost? Using tools originally devised for demographic research, we model the dynamics of the very initial spread of a useful novelty in a network. The network structure has a strong impact on these dynamics by affecting the effective network size through random effects. This effective network size, which correlates with the probability that a novelty spreads and is different from the actual size (i.e. number of nodes), varies with network structure. The effective size can even become independent of the actual network size and thus remain very small even for huge networks.

Details

einblenden:
ausblenden:
Sprache(n): eng - English
 Datum: 2018-02-072018-10-092018-11-122018-11
 Publikationsstatus: Erschienen
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: -
 Identifikatoren: DOI: 10.1371/journal.pcbi.1006559
 Art des Abschluß: -

Veranstaltung

einblenden:

Entscheidung

einblenden:

Projektinformation

einblenden:

Quelle 1

einblenden:
ausblenden:
Titel: PLoS Computational Biology
Genre der Quelle: Zeitschrift
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: San Francisco, CA : Public Library of Science
Seiten: - Band / Heft: 14 (11) Artikelnummer: e1006559 Start- / Endseite: - Identifikator: ISSN: 1553-734X
CoNE: https://pure.mpg.de/cone/journals/resource/1000000000017180_1