Subcellular localization prediction of apoptosis proteins based on evolutionary information and support vector machine

@article{Xiang2017SubcellularLP,
  title={Subcellular localization prediction of apoptosis proteins based on evolutionary information and support vector machine},
  author={Qilin Xiang and Bo Liao and Xianhong Li and Huimin Xu and Jing Chen and Zhuoxing Shi and Qi Dai and Yuhua Yao},
  journal={Artificial intelligence in medicine},
  year={2017},
  volume={78},
  pages={
          41-46
        }
}
OBJECTIVES In this paper, a high-quality sequence encoding scheme is proposed for predicting subcellular location of apoptosis proteins. METHODS In the proposed methodology, the novel evolutionary-conservative information is introduced to represent protein sequences. Meanwhile, based on the proportion of golden section in mathematics, position-specific scoring matrix (PSSM) is divided into several blocks. Then, these features are predicted by support vector machine (SVM) and the predictive… CONTINUE READING
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