This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop e...
Jie Cheng, Russell Greiner, Jonathan Kelly, David ...
Background: One of the challenges of bioinformatics remains the recognition of short signal sequences in genomic DNA such as donor or acceptor splice sites, splicing enhancers or ...
Jens Keilwagen, Jan Grau, Stefan Posch, Ivo Grosse
Background: Inference of population stratification and individual admixture from genetic markers is an integrative part of a study in diverse situations, such as association mappi...
Background: There have been many algorithms and software programs implemented for the inference of multiple sequence alignments of protein and DNA sequences. The "true" ...
Paulo A. S. Nuin, Zhouzhi Wang, Elisabeth R. M. Ti...
Despite advances in the application of automated statistical and machine learning techniques to system log and trace data there will always be a need for human analysis of machine...