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Positive sample only learning (PSOL) for predicting RNA genes in E. coli

  • Richard F. Meraz*
  • , Xiaofeng He
  • , Chris H.Q. Ding
  • , Stephen R. Holbrook
  • *此作品的通讯作者
  • Lawrence Berkeley National Laboratory

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

RNA genes lack most of the signals used for protein gene identification. A major shortcoming of previous discriminative methods to distinguish functional RNA (fRNA) genes from other non-coding genomic sequences is that only positive examples of fRNAs are known; there are no confirmed negatives - only intergenic sequences that may be positive or negative. To address this problem we developed the "Positive Sample Only Learning" (PSOL) method. This method can identify the most likely negative examples from an unlabeled set and is therefore able to distinguish putative functional RNA genes from other non-coding sequence. We compare RNA gene predictions using the PSOL method with previous large-scale analyses of the E. coli K12 genome.

源语言英语
主期刊名Proceedings - 2004 IEEE Computational Systems Bioinformatics Conference, CSB 2004
535-538
页数4
出版状态已出版 - 2004
已对外发布
活动Proceedings - 2004 IEEE Computational Systems Bioinformatics Conference, CSB 2004 - Stanford, CA, 美国
期限: 16 8月 200419 8月 2004

出版系列

姓名Proceedings - 2004 IEEE Computational Systems Bioinformatics Conference, CSB 2004

会议

会议Proceedings - 2004 IEEE Computational Systems Bioinformatics Conference, CSB 2004
国家/地区美国
Stanford, CA
时期16/08/0419/08/04

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