Background: We present a general approach to perform association analyses in pedigrees of arbitrary size and structure, which also allows for a mixture of pedigree members and ind...
Kristina Allen-Brady, Jathine Wong, Nicola J. Camp
Background: A key challenge in metabonomics is to uncover quantitative associations between multidimensional spectroscopic data and biochemical measures used for disease risk asse...
Background: General protein evolution models help determine the baseline expectations for the evolution of sequences, and they have been extensively useful in sequence analysis an...
Andy Pang, Andrew D. Smith, Paulo A. S. Nuin, Elis...
It is well-known that, in unidentifiable models, the Bayes estimation provides much better generalization performance than the maximum likelihood (ML) estimation. However, its ac...
Recent research in frequent pattern mining (FPM) has shifted from obtaining the complete set of frequent patterns to generating only a representative (summary) subset of frequent ...