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Predicting subcellular location of apoptosis proteins based on wavelet transform and support vector machine

机译：基于小波变换和支持向量机的凋亡蛋白亚细胞定位预测

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Apoptosis proteins have a central role in the development and homeostasis of an organism. These proteins are very important for understanding the mechanism of programmed cell death. As a result of genome and other sequencing projects, the gap between the number of known apoptosis protein sequences and the number of known apoptosis protein structures is widening rapidly. Because of this extremely unbalanced state, it would be worthwhile to develop a fast and reliable method to identify their subcellular locations so as to gain better insight into their biological functions. In view of this, a new method, in which the support vector machine combines with discrete wavelet transform, has been developed to predict the subcellular location of apoptosis proteins. The results obtained by the jackknife test were quite promising, and indicated that the proposed method can remarkably improve the prediction accuracy of subcellular locations, and might also become a useful high-throughput tool in characterizing other attributes of proteins, such as enzyme class, membrane protein type, and nuclear receptor subfamily according to their sequences.
机译：凋亡蛋白在生物体的发育和体内平衡中起着核心作用。这些蛋白质对于理解程序性细胞死亡的机制非常重要。作为基因组和其他测序项目的结果，已知凋亡蛋白序列的数目与已知凋亡蛋白结构的数目之间的差距正在迅速扩大。由于这种极端不平衡的状态，因此有必要开发一种快速可靠的方法来鉴定其亚细胞位置，从而更好地了解其生物学功能。鉴于此，已经开发了一种新方法，其中支持向量机与离散小波变换相结合，可以预测凋亡蛋白的亚细胞位置。通过折刀试验获得的结果非常有前景，表明该方法可以显着提高亚细胞位置的预测准确性，也可能成为表征蛋白质其他属性（例如酶类别，膜）的有用的高通量工具。蛋白质类型和核受体亚家族（根据其序列）。

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