Optimizing Experimental Design in Genetics

Researchers in the life sciences (i.e., healthcare and agriculture) commonly use heuristics to process and interpret the vast amount of available DNA sequence data. The application of discrete optimization techniques, such as mixed-integer programming (MIP), remains largely unexplored and has the po...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Journal of optimization theory and applications 2013-05, Vol.157 (2), p.520-532
Hauptverfasser:	McClosky, B., Tanksley, S. D.
Format:	Artikel
Sprache:	eng
Schlagworte:	Applications of Mathematics Calculus of Variations and Optimal Control Optimization Deoxyribonucleic acid Engineering Experiments Genetics Genomes Genomics Health care Heuristic Integer programming Life sciences Mathematics Mathematics and Statistics Operations Research/Decision Theory Optimization Optimization techniques Population Programming Quantitative genetics Statistical power Studies Theory of Computation Transforms
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!