Methodology article
Improving the specificity of high-throughput ortholog prediction
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* Corresponding author: Fiona SL Brinkman brinkman@sfu.ca
- † Equal contributors
1 Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, BC, Canada
2 Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
3 Canada's Michael Smith Genome Sciences Centre, 570 W. 7th Avenue, Vancouver, BC, Canada
BMC Bioinformatics 2006, 7:270 doi:10.1186/1471-2105-7-270
Published: 28 May 2006Additional files
Additional file 1:
Supplementary Figures. Supplementary Figure 1. Ratio1, Ratio2 and Ratio3 histograms of the P. putida – P. syringae – E. coli putative orthologous sets summarizing results of a true negative introduction analysis. Supplementary Figure 2. Ratio2 and Ratio3 histograms of the mouse-rat-human putative orthologous sets indicating the average proportion of true negatives observed in our simulation of an incomplete genome through the iterative introduction of a mouse (ingroup1) paralog in randomly selected ortholog sets. Supplementary Figure 3. Histograms of Ortholuge Ratios 1, 2, and 3 for the mouse-rat-human RBH RefSeq nucleotide dataset. Supplementary Figure 4. Histograms of Ortholuge Ratios 1, 2, and 3 for the mouse-rat-human OrthoMCL protein dataset.
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