Metagenome Fragment Binning Based on Characterization Vectors

摘要：

We propose an approach for metagenome fragment binning using support vector machine (SVM) and characterization vectors. We developed this method to overcome the limitation of the composition-based approach using k-mer features to perform the binning process, particularly for short fragments. We take advantage of characterization vectors, which consider global information of DNA fragments without performing sequence alignments. The global information of sequences can be represented by twelve-dimensional information. Our experiments show that this method is highly accurate for binning metagenome fragments at the genus level with fragment lengths > 500 bp for datasets representing known and new organisms. This approach is promising for extension to other taxonomy levels.

关键词： metagenome binning characterization vector support vector machine

作者: Wisnu Ananta Kusuma Yutaka Akiyama

作者单位: Department of Computer Science, Graduate School of Information Science and Engineering, Tokyo Institute of Technology Tokyo, Japan

会议类型: 国际会议

会议名称: International Conference on Bioinformatics and Biomedical Technology(ICBBT 2011)(2011年生物信息与生物医药技术国际会议)

会议地点: 三亚

会议语种:英文

页码: 50-54

在线出版日期: 2011-03-25（万方平台首次上网日期，不代表论文的发表时间）