Afhalen na 1 uur in een winkel met voorraad
Gratis thuislevering in België vanaf € 30
Ruim aanbod met 7 miljoen producten

Afhalen na 1 uur in een winkel met voorraad
Gratis thuislevering in België vanaf € 30
Ruim aanbod met 7 miljoen producten

Winkels

Verlanglijstje

Winkels

Verlanglijstje

Zoeken

Volg ons op

140 winkels

Wist je dat er in Vlaanderen voor iedereen een Standaard Boekhandel is binnen een straal van 7 km?

Vind hier een winkel

€ 157,95

+ 315 punten

Uitvoering

Levering 2 à 3 weken

Eenvoudig bestellen

Veilig betalen

Gratis thuislevering vanaf € 30 (via bpost)

Gratis levering in je Standaard Boekhandel

Omschrijving

The field of molecular evolution has experienced explosive growth in recent years due to the rapid accumulation of genetic sequence data, continuous improvements to computer hardware and software, and the development of sophisticated analytical methods. The increasing availability of large genomic data sets requires powerful statistical methods to analyze and interpret them, generating both computational and conceptual challenges for the field.

Computational Molecular Evolution provides an up-to-date and comprehensive coverage of modern statistical and computational methods used in molecular evolutionary analysis, such as maximum likelihood and Bayesian statistics. Yang describes the models, methods and algorithms that are most useful for analysing the ever-increasing supply of molecular sequence data, with a view to furthering our understanding of the evolution of genes and genomes. The book emphasizes essential concepts rather than mathematical proofs. It includes detailed derivations and implementation details, as well as numerous illustrations, worked examples, and exercises. It will be of relevance and use to students and professional researchers (both empiricists and theoreticians) in the fields of molecular phylogenetics, evolutionary biology, population genetics, mathematics, statistics and computer science. Biologists who have used phylogenetic software programs to analyze their own data will find the book particularly rewarding, although it should appeal to anyone seeking an authoritative overview of this exciting area of computational biology.