Recognition of Mitochondrial Proteins in Plasmodium Based on the Tripeptide Composition.
Recognition of Mitochondrial Proteins in Plasmodium Based on the Tripeptide Composition.
复制标题
DOI：
10.3389/fcell.2020.578901
复制
发表时间：
2020
影响因子：
5.5
通讯作者：
Wang J
中科院分区：
文献类型：
--
作者：
Bian H;Guo M;Wang J
线粒体在真核细胞，特别是疟原虫细胞中发挥着重要作用。它们具有一些不寻常的进化和功能特征，对于疾病诊断和药物设计至关重要。因此，预测疟原虫线粒体蛋白质是一项有价值的工作。然而，现有的计算方法只能预测恶性疟原虫（Plasmodium falciparum，简称P. falciparum）的线粒体蛋白，且准确性较低。非常需要设计一种具有高准确度的分类器来预测所有疟原虫物种的线粒体蛋白，而不仅仅是恶性疟原虫。提出了一种新的预测疟原虫线粒体蛋白质的方法PM-OTC。PM-OTC使用支持向量机（SVM）作为分类器，选择的三肽组合物作为特征。采用5重交叉验证方法对PM-OTC进行训练和测试。结果表明，PM-OTC的准确度达到94.91%，性能优于其他方法上级。
Mitochondria play essential roles in eukaryotic cells, especially in Plasmodium cells. They have several unusual evolutionary and functional features that are incredibly vital for disease diagnosis and drug design. Thus, predicting mitochondrial proteins of Plasmodium has become a worthwhile work. However, existing computational methods can only predict mitochondrial proteins of Plasmodium falciparum (P. falciparum for short), and these methods have low accuracy. It is highly desirable to design a classifier with high accuracy for predicting mitochondrial proteins for all Plasmodium species, not only P. falciparum. We proposed a novel method, named as PM-OTC, for predicting mitochondrial proteins in Plasmodium. PM-OTC uses the Support Vector Machine (SVM) as the classifier and the selected tripeptide composition as the features. We adopted the 5-fold cross-validation method to train and test PM-OTC. Results demonstrate that PM-OTC achieves an accuracy of 94.91%, and performances of PM-OTC are superior to other methods.
登录
查看更多内容
DOI：
10.1093/bioinformatics/bts565
发表时间：
2012-12-01
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Fu L;Niu B;Zhu Z;Wu S;Li W
通讯作者：
Li W
影响因子：
5.8
作者：
Chou, KC
通讯作者：
Chou, KC
影响因子：
81.5
作者：
Phillips, Margaret A.;Burrows, Jeremy N.;Wells, Timothy N. C.
通讯作者：
Wells, Timothy N. C.
影响因子：
5.8
作者：
Murakami, Yoichi;Mizuguchi, Kenji
通讯作者：
Mizuguchi, Kenji
影响因子：
5.6
作者：
NAKASHIMA, H;NISHIKAWA, K
通讯作者：
NISHIKAWA, K