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Simultaneous inference of biological networks of multiple species from genome-wide data and evolutionary information: a semi-supervised approach

机译:从全基因组数据和进化信息同时推断多种物种的生物网络:一种半监督方法

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摘要

Motivation: The existing supervised methods for biological network inference work on each of the networks individually based only on intra-species information such as gene expression data. We believe that it will be more effective to use genomic data and cross-species evolutionary information from different species simultaneously, rather than to use the genomic data alone.
机译:动机:现有的受监督的生物网络推理方法仅基于种内信息(例如基因表达数据)在每个网络上单独起作用。我们相信,同时使用来自不同物种的基因组数据和跨物种进化信息将比单独使用基因组数据更有效。

著录项

  • 来源
    《Bioinformatics》 |2009年第22期|p.2962-2968|共7页
  • 作者单位

    1IBM Research, Tokyo Research Laboratory, 1623-14 Shimo-tsuruma, Yamato, Kanagawa, 242-8502 Japan, 2Mines ParisTech, Centre for Computational Biology, 35 rue Saint-Honore, F-77305 Fontainebleau Cedex, France, 3Institut Curie, 4INSERM, U900, F-75248, Paris, France, 5Ochanomizu University, Center for Informational Biology, 2-1-1 Ohtsuka, Bunkyo-ku, Tokyo 112-8610, 6Tokyo Institute of Technology, Department of Computer Science, 2-12-1, O-okayama, Meguro-ku, Tokyo 152-8552 and 7National Institute of Advanced Industrial Science and Technology, Computational Biology Research Center (AIST), 2-42 Aomi, Koto-ku, Tokyo 135-0064, Japan;

  • 收录信息 美国《科学引文索引》(SCI);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
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