All Outputs (2)

Pertinent background knowledge for learning protein grammars (2006)
Book Chapter
Bryant, C., Fredouille, D., Wilson, A., Jayawickreme, C., Jupe, S., & Topp, S. (2006). Pertinent background knowledge for learning protein grammars. In J. Fürnkranz, T. Scheffer, & M. Spiliopoulou (Eds.), Machine learning: ECML 2006 (54-65). Berlin / Heidelberg, Germany: Springer. https://doi.org/10.1007/11871842_10

We are interested in using Inductive Logic Programming(ILP) to infer grammars representing sets of protein sequences. ILP takes as input both examples and background knowledge predicates. This work is a first step in optimising the choice of backgrou... Read More about Pertinent background knowledge for learning protein grammars.

A first step towards learning which uORFs regulate gene expression (2006)
Journal Article
Bryant, C., Kemp, G., & Cvijovic, M. (2006). A first step towards learning which uORFs regulate gene expression. Journal of Integrative Bioinformatics, 3(2), 31. https://doi.org/10.2390/biecoll-jib-2006-31

We have taken a first step towards learning which upstream Open Reading Frames (uORFs) regulate gene expression (i.e., which uORFs are functional) in the yeast Saccharomyces cerevisiae. We do this by integrating data from several resources and combin... Read More about A first step towards learning which uORFs regulate gene expression.