Identifying a few foot-and-mouth disease virus signature nucleotide strings for computational genotyping

Background: Serotypes of the Foot-and-Mouth disease viruses (FMDVs) were generally determined by biological experiments. The computational genotyping is not well studied even with the availability of whole viral genomes, due to uneven evolution among genes as well as frequent genetic recombination. Naively using sequence comparison for genotyping is only able to achieve a limited extent of success. Results: We used 129 FMDV strains with known serotype as training strains to select as many as 140 most serotype-specific nucleotide strings. We then constructed a linear-kernel Support Vector Machine classifier using these 140 strings. Under the leave-one-out cross validation scheme, this classifier was able to assign correct serotype to 127 of these 129 strains, achieving 98.45% accuracy. It also assigned serotype correctly to an independent test set of 83 other FMDV strains downloaded separately from NCBI GenBank. Conclusion: Computational genotyping is much faster and much cheaper than ...

• Type: Journal
• Year: 2008
• Where: BMCBI
• Authors: Guohui Lin, Zhipeng Cai, Junfeng Wu, Xiu-Feng Wan, Lizhe Xu, Randy Goebel
• Keywords: BMCBI 2008, Disease, FMDV Strains, Serotypes