Homology Induction: the use of machine learning to improve sequence similarity searches

Karwath, A. King, R. Homology induction: the use of machine learning to improve sequence similarity searches. BMC Bioinformatics. 23rd April 2002. 3:11 Additional File Describes the title organims species declaration in one string [http://www.biomedcentral.com/content/supplementary/1471- 2105-3-11-S1.doc] Sponsorship: Andreas Karwath and Ross D. King were supported by the EPSRC grant GR/L62849.

Learning styles and performance in the introductory programming sequence

Thomas, L., Ratcliffe, M., Woodbury, J., and Jarman, E. 2002. Learning styles and performance in the introductory programming sequence. SIGCSE Bull. 34, 1 (Mar. 2002), 33-37.

Analysis of Sequence Periodicity in E. coli Proteins: Empirical Investigation of the ?Duplication and Divergence? Theory of Protein Evolution

Gatherer, D., and McEwan, N.R. (2003). Analysis of sequence periodicity in E. coli proteins: empirical investigation of the 'duplication and divergence' theory of protein evolution. Journal of Molecular Evolution 57, 149-158. RAE2008

The performance of models relating species geographical distributions to climate is independent of trophic level

Brian Huntley, Rhys E. Green, Yvonne C. Collingham, Jane K. Hill, Stephen G. Willis , Patrick J. Bartlein, Wolfgang Cramer, Ward J. M. Hagemeijer and Christopher J. Thomas (2004). The performance of models relating species geographical distributions to climate is independent of trophic level. Ecology Letters, 7(5), 417-426. Sponsorship: NERC (awards: GR9/3016, GR9/04270, GR3/12542, NER/F/S/2000/00166) / RSPB RAE2008

A Phylogenetic Mixture Model for Detecting Pattern-Heterogeneity in Gene Sequence or Character-State Data

Mark Pagel, Andrew Meade (2004). A phylogenetic mixture model for detecting pattern-heterogeneity in gene sequence or character-state data. Systematic Biology, 53(4), 571-581. RAE2008