All Outputs (4)

Using mRNA secondary structure predictions improves recognition of known yeast functional uORFs (2008)
Book Chapter
Selpi, S., Bryant, C., & Kemp, G. (2008). Using mRNA secondary structure predictions improves recognition of known yeast functional uORFs. In L. Wehenkel, P. Geurts, Y. Moreau, & F. d'Alche-Buc (Eds.), Proceedings of 2nd International Workshop on Machine Learning in Systems Biology (85-94). University of Liege

We are interested in using inductive logic programming ILP)to generate rules for recognising functional upstream open reading frames (uORFs) in the yeast Saccharomyces cerevisiae. This paper empirically investigates whether providing an ILP system wi... Read More about Using mRNA secondary structure predictions improves recognition of known yeast functional uORFs.

An Inductive Logic Programming Approach to Learning which uORFs Regulate Gene Expression (2008)
Thesis
Selpi. (2008). An Inductive Logic Programming Approach to Learning which uORFs Regulate Gene Expression. (Thesis). The Robert Gordon University

Some upstream open reading frames (uORFs) regulate gene expression (i.e. they are functional) and can play key roles in keeping organisms healthy. However, how uORFs are involved in gene regulation is not het fully understood. In order to get a compl... Read More about An Inductive Logic Programming Approach to Learning which uORFs Regulate Gene Expression.

Inferring the function of genes from synthetic lethal mutations (2008)
Conference Proceeding
Ray, O., & Bryant, C. (2008). Inferring the function of genes from synthetic lethal mutations. In F. Xhafa, & L. Barolli (Eds.), Complex, Intelligent and Software Intensive Systems (667-671). https://doi.org/10.1109/CISIS.2008.124

Techniques for detecting synthetic lethal mutations in double gene deletion experiments are emerging as powerful tool for analysing genes in parallel or overlapping pathways with a shared function. This paper introduces a logic-based approach that us... Read More about Inferring the function of genes from synthetic lethal mutations.

L-modified ILP evaluation functions for positive-only biological grammar learning (2008)
Book Chapter
Mamer, T., Bryant, C., & McCall, J. (2008). L-modified ILP evaluation functions for positive-only biological grammar learning. In F. Zelezny, & N. Lavrac (Eds.), Inductive logic programming (176-191). Berlin / Heidelberg, Germany: Springer. https://doi.org/10.1007/978-3-540-85928-4_16

We identify a shortcoming of a standard positive-only clause evaluation function within the context of learning biological grammars. To overcome this shortcoming we propose L-modification, a modification to this evaluation function such that the leng... Read More about L-modified ILP evaluation functions for positive-only biological grammar learning.