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In this paper, we design a novel deep learning architecture, so-called DeepFrag-k, which identifies fold discriminative features at fragment level to improve the accuracy of protein fold recognition. DeepFrag-k is composed of two stages: the first stage employs a multi-modal Deep Belief Network (DBN) to predict the potential structural fragments given a sequence, represented as a fragment vector, and then the second stage uses a deep convolutional neural network (CNN) to classify the fragment vector into the corresponding fold.<\/jats:p>\n<\/jats:sec><jats:sec>\n<jats:title>Results<\/jats:title>\n<jats:p>Our results show that DeepFrag-k yields 92.98<jats:italic>%<\/jats:italic> accuracy in predicting the top-100 most popular fragments, which can be used to generate discriminative fragment feature vectors to improve protein fold recognition.<\/jats:p>\n<\/jats:sec><jats:sec>\n<jats:title>Conclusions<\/jats:title>\n<jats:p>There is a set of fragments that can serve as structural \u201ckeywords\u201d distinguishing between major protein folds. The deep learning architecture in DeepFrag-k is able to accurately identify these fragments as structure features to improve protein fold recognition.<\/jats:p>\n<\/jats:sec>","DOI":"10.1186\/s12859-020-3504-z","type":"journal-article","created":{"date-parts":[[2020,11,18]],"date-time":"2020-11-18T04:14:07Z","timestamp":1605672847000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["DeepFrag-k: a fragment-based deep learning approach for protein fold recognition"],"prefix":"10.1186","volume":"21","author":[{"given":"Wessam","family":"Elhefnawy","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Min","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianxin","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0178-1876","authenticated-orcid":false,"given":"Yaohang","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,11,18]]},"reference":[{"issue":"8","key":"3504_CR1","doi-asserted-by":"publisher","first-page":"1093","DOI":"10.1016\/S0969-2126(97)00260-8","volume":"5","author":"C Orengo","year":"1997","unstructured":"Orengo C, Michie A, Jones S, Jones D, Swindells M, Thornton J. 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