首页> 外文会议>International Conference on Intelligent Systems for Molecular Biology >Accelerating Protein Classification Using Suffix Trees
【24h】

Accelerating Protein Classification Using Suffix Trees

机译:使用后缀树加速蛋白质分类

获取原文

摘要

Position-specific scoring matrices have been used extensively to recognize highly conserved protein regions. We present a method for accelerating these searches using a suffix tree data structure computed from the sequences to be searched. Building on earlier work that allows evaluation of a scoring matrix to be stopped early, the suffix tree-based method excludes many protein segments from consideration at once by pruning entire subtrees. Although suffix trees are usually expensive in space, the fact that scoring matrix evaluation requires an in-order traversal allows nodes to be stored more compactly without loss of speed, and our implementation requires only 17 bytes of primary memory per input symbol. Searches are accelerated by up to a factor of ten.
机译:定位特异性评分矩阵已被广泛用于识别高度保守的蛋白质区域。我们介绍了一种使用从要搜索的序列计算的后缀树数据结构加速这些搜索的方法。在早期的工作中建立允许早期评估得分矩阵,基于后缀的树木的方法通过修剪整个子树来不包括考虑的许多蛋白质区段。虽然后缀树通常在空间中昂贵,但得分矩阵评估需要按顺序遍历允许节点更加紧凑地存储而不会损失速度,并且我们的实现每输入符号只需要17个字节的主存储器。搜索达到10倍。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号