A novel approach to image enhancement using the generalized maximum likelihood criterion

Author(s):  
N.M. Namazi ◽  
N.S. Goksel ◽  
I. Miskioglu
2006 ◽  
Vol 04 (03) ◽  
pp. 639-647 ◽  
Author(s):  
ELEAZAR ESKIN ◽  
RODED SHARAN ◽  
ERAN HALPERIN

The common approaches for haplotype inference from genotype data are targeted toward phasing short genomic regions. Longer regions are often tackled in a heuristic manner, due to the high computational cost. Here, we describe a novel approach for phasing genotypes over long regions, which is based on combining information from local predictions on short, overlapping regions. The phasing is done in a way, which maximizes a natural maximum likelihood criterion. Among other things, this criterion takes into account the physical length between neighboring single nucleotide polymorphisms. The approach is very efficient and is applied to several large scale datasets and is shown to be successful in two recent benchmarking studies (Zaitlen et al., in press; Marchini et al., in preparation). Our method is publicly available via a webserver at .


2015 ◽  
Vol 33 (7) ◽  
pp. 1300-1307 ◽  
Author(s):  
Patricia Layec ◽  
Amirhossein Ghazisaeidi ◽  
Gabriel Charlet ◽  
Jean-Christophe Antona ◽  
Sebastien Bigo

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