...
首页> 外文期刊>Bioinformatics >pLoc-mAnimal: predict subcellular localization of animal proteins with both single and multiple sites
【24h】

pLoc-mAnimal: predict subcellular localization of animal proteins with both single and multiple sites

机译:ploc-manimal:预测单个和多个位点的动物蛋白的亚细胞定位

获取原文
获取原文并翻译 | 示例
           

摘要

Cells are deemed the basic unit of life. However, many important functions of cells as well as their growth and reproduction are performed via the protein molecules located at their different organelles or locations. Facing explosive growth of protein sequences, we are challenged to develop fast and effective method to annotate their subcellular localization. However, this is by no means an easy task. Particularly, mounting evidences have indicated proteins have multi-label feature meaning that they may simultaneously exist at, or move between, two or more different subcellular location sites. Unfortunately, most of the existing computational methods can only be used to deal with the single-label proteins. Although the 'iLoc-Animal' predictor developed recently is quite powerful that can be used to deal with the animal proteins with multiple locations as well, its prediction quality needs to be improved, particularly in enhancing the absolute true rate and reducing the absolute false rate.
机译:细胞被认为是生命的基本单位。然而,通过位于其不同的细胞器或位置的蛋白质分子进行细胞的许多重要功能以及它们的生长和繁殖。面对蛋白质序列的爆炸性生长,我们受到开发快速有效的方法来挑战其亚细胞定位的方法。但是,这绝不是一项简单的任务。特别地,安装证据表明蛋白质具有多标签特征,这意味着它们可以同时存在于两个或更多个不同的亚细胞位置位点处。不幸的是,大多数现有的计算方法只能用于处理单标签蛋白。尽管最近开发的“ILOC-DATOLAL”预测因子也可以用于处理具有多个位置的动物蛋白质,但需要改善其预测质量,特别是提高绝对真实率并降低绝对假速率。

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