PTPD: predicting therapeutic peptides by deep learning and word2vec
Abstract * Background In the search for therapeutic peptides for disease treatments, many efforts have been made to identify various functional peptides from large numbers of peptide sequence databases. In this paper, we propose an effective computational model that uses deep learning and word2vec t...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2019-09-01
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| Series: | BMC Bioinformatics |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s12859-019-3006-z |