Expression, purification and structural analysis of the Pyrococcus abyssi RNA binding protein PAB1135 |
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Authors: | Juliana S Luz João ARG Barbosa Celso RR Ramos Carla C Oliveira |
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Affiliation: | 1. Department of Animal and Dairy Science, University of Georgia, 30602, Athens, GA, USA 2. Institute of Bioinformatics, University of Georgia, 30602, Athens, GA, USA 3. Department of Statistics, University of Georgia, 30602, Athens, GA, USA
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Abstract: | Background Epistatic interactions of multiple single nucleotide polymorphisms (SNPs) are now believed to affect individual susceptibility to common diseases. The detection of such interactions, however, is a challenging task in large scale association studies. Ant colony optimization (ACO) algorithms have been shown to be useful in detecting epistatic interactions. Findings AntEpiSeeker, a new two-stage ant colony optimization algorithm, has been developed for detecting epistasis in a case-control design. Based on some practical epistatic models, AntEpiSeeker has performed very well. Conclusions AntEpiSeeker is a powerful and efficient tool for large-scale association studies and can be downloaded from http://nce.ads.uga.edu/~romdhane/AntEpiSeeker/index.html. |
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