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In this paper, we introduce the anticancer peptide secondary structures as additional features and propose an effective computational model, CL-ACP, that uses a combined network and attention mechanism to predict anticancer peptides.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The CL-ACP model uses secondary structures and original sequences of anticancer peptides to construct the feature space. The long short-term memory and convolutional neural network are used to extract the contextual dependence and local correlations of the feature space. Furthermore, a multi-head self-attention mechanism is used to strengthen the anticancer peptide sequences. Finally, three categories of feature information are classified by cascading. CL-ACP was validated using two types of datasets, anticancer peptide datasets and antimicrobial peptide datasets, on which it achieved good results compared to previous methods. CL-ACP achieved the highest AUC values of 0.935 and 0.972 on the anticancer peptide and antimicrobial peptide datasets, respectively.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>CL-ACP can effectively recognize antimicrobial peptides, especially anticancer peptides, and the parallel combined neural network structure of CL-ACP does not require complex feature design and high time cost. It is suitable for application as a useful tool in antimicrobial peptide design.<\/jats:p><\/jats:sec>","DOI":"10.1186\/s12859-021-04433-9","type":"journal-article","created":{"date-parts":[[2021,10,20]],"date-time":"2021-10-20T11:51:56Z","timestamp":1634730716000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["CL-ACP: a parallel combination of CNN and LSTM anticancer peptide recognition model"],"prefix":"10.1186","volume":"22","author":[{"given":"Huiqing","family":"Wang","sequence":"first","affiliation":[]},{"given":"Jian","family":"Zhao","sequence":"additional","affiliation":[]},{"given":"Hong","family":"Zhao","sequence":"additional","affiliation":[]},{"given":"Haolin","family":"Li","sequence":"additional","affiliation":[]},{"given":"Juan","family":"Wang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,10,20]]},"reference":[{"key":"4433_CR1","doi-asserted-by":"crossref","unstructured":"Domingues MM, Fel\u00edcio M, Gonalves S: Antimicrobial peptides: effect on bacterial cells: methods and protocols. 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