ACPred-FL: a sequence-based predictor using effective feature representation to improve the prediction of anti-cancer peptides

Wei Leyi; Zhou Chen; Chen Huangrong; Song Jiangning; Su Ran

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ACPred-FL: a sequence-based predictor using effective feature representation to improve the prediction of anti-cancer peptides

机译：ACPRED-FL：使用有效特征表示的基于序列的预测因子，以改善抗癌肽的预测

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Motivation: Anti-cancer peptides (ACPs) have recently emerged as promising therapeutic agents for cancer treatment. Due to the avalanche of protein sequence data in the post-genomic era, there is an urgent need to develop automated computational methods to enable fast and accurate identification of novel ACPs within the vast number of candidate proteins and peptides.

机译：刺激：抗癌肽（ACPs）最近被出现为癌症治疗的有前途的治疗剂。由于后基因组时代的蛋白质序列数据的雪崩，迫切需要开发自动计算方法，以便在大量候选蛋白和肽内快速准确地鉴定新的ACP。

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《Bioinformatics》 |2018年第23期|共10页
作者
Wei Leyi; Zhou Chen; Chen Huangrong; Song Jiangning; Su Ran;
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作者单位

Tianjin Univ Sch Comp Sci &

Technol Tianjin Peoples R China;

Tianjin Univ Sch Comp Sci &

Technol Tianjin Peoples R China;

Tianjin Univ Sch Comp Sci &

Technol Tianjin Peoples R China;

Monash Univ Fac Informat Technol Biomed Discovery Inst Clayton Vic 3800 Australia;

Tianjin Univ Sch Comp Software Tianjin Peoples R China;

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原文格式 PDF
正文语种 eng
中图分类生物工程学（生物技术）;
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专利

1. ACPred-FL: a sequence-based predictor using effective feature representation to improve the prediction of anti-cancer peptides [J] . Wei Leyi, Zhou Chen, Chen Huangrong, Bioinformatics . 2018,第23期

机译：ACPRED-FL：使用有效特征表示的基于序列的预测因子，以改善抗癌肽的预测
2. Meta-iPVP: a sequence-based meta-predictor for improving the prediction of phage virion proteins using effective feature representation [J] . Charoenkwan Phasit, Nantasenamat Chanin, Hasan Md. Mehedi, Journal of Computer-Aided Molecular Design . 2020,第10期

机译：Meta-IPVP：使用有效特征表示改善序列的元预测器，用于改善噬菌体病毒蛋白蛋白的预测
3. CPPred-FL: a sequence-based predictor for large-scale identification of cell-penetrating peptides by feature representation learning [J] . Xiaoli Qiang, Chen Zhou, Xiucai Ye, Briefings in bioinformatics . 2020,第1期

机译：CPPRED-FL：基于序列的预测因子，用于通过特征表示学习进行细胞穿透肽的大规模鉴定
4. A novel method to improve recognition of antimicrobial peptides through distal sequence-based features [C] . Veltri Daniel, Kamath Uday, Shehu Amarda IEEE International Conference on Bioinformatics and Biomedicine . 2014

机译：通过基于远端序列的特征提高对抗菌肽的识别的新方法
5. Effective energy functions for protein structure prediction based on predicted structural features [D] . Randall, Arlo 2008

机译：基于预测结构特征的蛋白质结构预测的有效能量函数
6. ACPred-FL: a sequence-based predictor using effective feature representation to improve the prediction of anti-cancer peptides [O] . Leyi Wei, Chen Zhou, Huangrong Chen, -1

机译：ACPred-FL：基于序列的预测子使用有效的特征表示来改进抗癌肽的预测
7. ACPred-FL: a sequence-based predictor using effective feature representation to improve the prediction of anti-cancer peptides [O] . Leyi Wei, Chen Zhou, Huangrong Chen, 2018

机译：ACPRED-FL：使用有效特征表示的基于序列的预测因子，以改善抗癌肽的预测

ACPred-FL: a sequence-based predictor using effective feature representation to improve the prediction of anti-cancer peptides

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