Q
Quan Zou
Researcher at University of Electronic Science and Technology of China
Publications - 445
Citations - 14686
Quan Zou is an academic researcher from University of Electronic Science and Technology of China. The author has contributed to research in topics: Computer science & Medicine. The author has an hindex of 58, co-authored 298 publications receiving 10507 citations. Previous affiliations of Quan Zou include Nankai University & Xiamen University.
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Biological functions of microRNAs: a review
TL;DR: The diverse roles of miRNAs in disease are discussed, including differentiation and development, metabolism, proliferation, apoptotic cell death, viral infection and tumorgenesis.
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Gene2vec: gene subsequence embedding for prediction of mammalian N6-methyladenosine sites from mRNA.
TL;DR: This work developed a model inferred from a larger sequence shifting window that can predict m6A accurately and robustly and evaluated these predictors mentioned above on a rigorous independent test data set and proved that the proposed method outperforms the state-of-the-art predictors.
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The Symbiodinium kawagutii genome illuminates dinoflagellate gene expression and coral symbiosis
Senjie Lin,Senjie Lin,Shifeng Cheng,Shifeng Cheng,Bo Song,Xiao Zhong,Xin Lin,Wujiao Li,Ling Li,Yaqun Zhang,Huan Zhang,Zhiliang Ji,Mei-Chun Cai,Yunyun Zhuang,Xinguo Shi,Lingxiao Lin,Lu Wang,Zhaobao Wang,Xin Liu,Sheng Yu,Peng Zeng,Han Hao,Quan Zou,Chengxuan Chen,Yanjun Li,Ying Wang,Chunyan Xu,Shanshan Meng,Xun Xu,Jun Wang,Jun Wang,Jun Wang,Huanming Yang,Huanming Yang,David A. Campbell,Nancy R. Sturm,Steve Dagenais-Bellefeuille,David Morse +37 more
TL;DR: The genome of the Coral symbiont Symbiodinium reveals fundamental aspects of the coral-alga symbiosis and finds biochemical complementarity between genomes of S. kawagutii and the anthozoan Acropora, providing a resource for studying the molecular basis and evolution of coral symbiosis.
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A novel features ranking metric with application to scalable visual and bioinformatics data classification
TL;DR: A Max-Relevance-Max-Distance (MRMD) feature ranking method, which balances accuracy and stability of feature ranking and prediction task, and runs faster than other filtering and wrapping methods, such as mRMR and Information Gain.
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Integrative approaches for predicting microRNA function and prioritizing disease-related microRNA using biological interaction networks
TL;DR: The existing computational approaches for predicting potential disease-related miRNA based on networks are summarized and the confronted difficulties that help understand the research status are presented.