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Biclustering analysis of transcriptome big data identifies condition-specific microRNA targets 원문보기

Nucleic acids research, v.47 no.9, 2019년, pp.e53 - e53  

Yoon, Sora (School of Life Sciences, Ulsan National Institute of Science and Technology, Ulsan 44919, Republic of Korea) ,  Nguyen, Hai C T (School of Life Sciences, Ulsan National Institute of Science and Technology, Ulsan 44919, Republic of Korea) ,  Jo, Woobeen (School of Life Sciences, Ulsan National Institute of Science and Technology, Ulsan 44919, Republic of Korea) ,  Kim, Jinhwan (School of Life Sciences, Ulsan National Institute of Science and Technology, Ulsan 44919, Republic of Korea) ,  Chi, Sang-Mun (School of Computer Science and Engineering, Kyungsung University, Busan 48434, Republic of Korea) ,  Park, Jiyoung (School of Life Sciences, Ulsan National Institute of Science and Technology, Ulsan 44919, Republic of Korea) ,  Kim, Seon-Young (Department of Functional Genomics, University of Science and Technology (UST), Daejeon 34141, Republic of Korea) ,  Nam, Dougu (School of Life Sciences, Ulsan National Institute of Science and Technology, Ulsan 44919, Republic of Korea)

Abstract AI-Helper 아이콘AI-Helper

AbstractWe present a novel approach to identify human microRNA (miRNA) regulatory modules (mRNA targets and relevant cell conditions) by biclustering a large collection of mRNA fold-change data for sequence-specific targets. Bicluster targets were assessed using validated messenger RNA (mRNA) target...

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