Structured Sparse Regularized TSK Fuzzy System for predicting therapeutic peptides
Author:
Affiliation:
1. Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, P.R.China
2. School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, P.R.China
Abstract
Funder
National Natural Science Foundation of China
Research Project of Wuxi Nursing Association
Publisher
Oxford University Press (OUP)
Subject
Molecular Biology,Information Systems
Link
https://academic.oup.com/bib/article-pdf/23/3/bbac135/43745178/bbac135.pdf
Reference40 articles.
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2. AntiAngioPred: a server for prediction of anti-angiogenic peptides;Ettayapuram Ramaprasad;PLoS One,2015
3. ACPred-FL: a sequence-based predictor using effective feature representation to improve the prediction of anti-cancer peptides;Wei;Bioinformatics,2018
4. PTPD: predicting therapeutic peptides by deep learning and word2vec;Wu;BMC Bioinformatics,2019
5. ACP-DL: a deep learning long short-term memory model to predict anticancer peptides using high-efficiency feature representation;Yi;Mol Ther Nucleic Acid,2019
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