• Corpus ID: 25307565

Retention Time of Peptides in Liquid Chromatography Is Well Estimated upon Deep Transfer Learning

@article{Ma2017RetentionTO,
  title={Retention Time of Peptides in Liquid Chromatography Is Well Estimated upon Deep Transfer Learning},
  author={Chunwei Ma and Zhiyong Zhu and Jun Ye and Jiarui Yang and Jianguo Pei and Shaohang Xu and Chang Yu and Fan Mo and Bo Wen and Siqi Liu},
  journal={arXiv: Quantitative Methods},
  year={2017}
}
A fully automatic prediction for peptide retention time (RT) in liquid chromatography (LC), termed as DeepRT, was developed using deep learning approach, an ensemble of Residual Network (ResNet) and Long Short-Term Memory (LSTM). In contrast to the traditional predictor based on the hand-crafted features for peptides, DeepRT learns features from raw amino acid sequences and makes relatively accurate prediction of peptide RTs with 0.987 R2 for unmodified peptides. Furthermore, by virtue of… 
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