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The existing in silico methods used for predicting the functions of lncRNA mainly rely on calculating the similarity of lncRNA or investigating whether an lncRNA can interact with a specific biomolecule or disease. In this work, we explored the functions of lncRNA from a different perspective: we presented a tool for predicting the interaction biomolecule type for a given lncRNA. For this purpose, we first investigated the main molecular mechanisms of the interactions of lncRNA\u2013RNA, lncRNA\u2013protein and lncRNA\u2013DNA. Then, we developed an ensemble deep learning model: lncIBTP (lncRNA Interaction Biomolecule Type Prediction). This model predicted the interactions between lncRNA and different types of biomolecules. On the 5-fold cross-validation, the lncIBTP achieves average values of 0.7042 in accuracy, 0.7903 and 0.6421 in macro-average area under receiver operating characteristic curve and precision\u2013recall curve, respectively, which illustrates the model effectiveness. Besides, based on the analysis of the collected published data and prediction results, we hypothesized that the characteristics of lncRNAs that interacted with DNA may be different from those that interacted with only RNA.<\/jats:p>","DOI":"10.1093\/bib\/bbaa228","type":"journal-article","created":{"date-parts":[[2020,8,25]],"date-time":"2020-08-25T11:10:05Z","timestamp":1598353805000},"source":"Crossref","is-referenced-by-count":28,"title":["Predicting the interaction biomolecule types for lncRNA: an ensemble deep learning approach"],"prefix":"10.1093","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4952-8095","authenticated-orcid":false,"given":"Yu","family":"Zhang","sequence":"first","affiliation":[{"name":"Shandong University, China and the MSc degree (distinction degree) from Imperial College London, UK, in 2017 and 2018, respectively. She is currently a PhD candidate in Nanyang Technological University, Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cangzhi","family":"Jia","sequence":"additional","affiliation":[{"name":"School of Mathematical Sciences from the Dalian University of Technology, in 2007. She is an associate professor with the School of Science, Dalian Maritime University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chee Keong","family":"Kwoh","sequence":"additional","affiliation":[{"name":"National University of Singapore, Singapore, in 1987 and 1991, respectively. He received the PhD degree from the Imperial College of Science, Technology and Medicine, University of London, in 1995"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2020,10,1]]},"reference":[{"issue":"39","key":"2021072112100122900_ref1","doi-asserted-by":"crossref","first-page":"5003","DOI":"10.1038\/onc.2014.456","article-title":"Junk DNA and the long non-coding RNA twist in cancer genetics","volume":"34","author":"Ling","year":"2015","journal-title":"Oncogene"},{"issue":"1","key":"2021072112100122900_ref2","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1093\/bib\/bbv031","article-title":"Revealing protein\u2013lncRNA interaction","volume":"17","author":"Ferre","year":"2016","journal-title":"Brief Bioinform"},{"issue":"4","key":"2021072112100122900_ref3","first-page":"558","article-title":"Long non-coding RNAs and complex diseases: from experimental results to computational 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