首页> 外文会议>Computational Intelligence in Bioinformatics and Computational Biology, 2009. CIBCB '09 >Detecting sequence and structure homology via an integrative kernel: A case-study in recognizing enzymes
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Detecting sequence and structure homology via an integrative kernel: A case-study in recognizing enzymes

机译:通过整合核检测序列和结构同源性:识别酶的案例研究

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Sequence and structure are complementary pieces of information that can be used to infer protein function. We study and compare sequence, structure and sequence-structure integrative kernels to recognize proteins with enzymatic function. Using a support-vector machine, we show that kernels that combine sequence and structure information typically perform better (AUC 0.73) at this task than kernels that exploit either type of information exclusively. We find that the feature space of structure kernels complements that of sequence kernels, making both sources of similarity more accessible to kernel methods.
机译:序列和结构是可以用来推断蛋白质功能的互补信息。我们研究和比较序列,结构和序列结构整合核,以识别具有酶促功能的蛋白质。使用支持向量机,我们证明了结合序列和结构信息的内核在此任务上的性能通常比专门利用这两种信息的内核更好(AUC 0.73)。我们发现,结构核的特征空间补充了序列核的特征空间,使两种相似性来源更易于内核方法访问。

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