Browsing by Author "Ruan, Yijun"

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  • Pseudogenes in the ENCODE regions: consensus annotation, analysis of transcription, and evolution
    Zheng, Deyou; Frankish, Adam; Baertsch, Robert; Kapranov, Philipp; Reymond, Alexandre; Choo, Siew Woh; Lu, Yontao; Denoeud, France; Antonarakis, Stylianos E.; Snyder, Michael; Ruan, Yijun; Wei, Chia-Lin; Gingeras, Thomas R.; Guigó Serra, Roderic; Harrow, Jennifer; Gerstein, Mark B. (Cold Spring Harbor Laboratory Press-CSHL Press, 2007)
    Arising from either retrotransposition or genomic duplication of functional genes, pseudogenes are “genomic fossils” valuable for exploring the dynamics and evolution of genes and genomes. Pseudogene identification is an ...
  • The GENCODE v7 catalog of human long noncoding RNAs: analysis of their gene structure, evolution, and expression
    Derrien, Thomas; Johnson, Rory; Bussotti, Giovanni, 1983-; Tanzer, Andrea; Djebali, Sarah; Tilgner, Hagen, 1980-; Guernec, Gregory; Martin, David; Merkel, Angelika; Knowles, David G.; Lagarde, Julien; Veeravalli, Lavanya; Ruan, Xiaoan; Ruan, Yijun; Lassmann, Timo; Carninci, Piero; Brown, James B.; Lipovich, Leonard; González, José M.; Thomas, Mark; Davis, Carrie A.; Shiekhattar, Ramin; Gingeras, Thomas R.; Hubbard, Tim J.; Notredame, Cedric; Harrow, Jennifer; Guigó Serra, Roderic (Cold Spring Harbor Laboratory Press (CSHL Press), 2012)
    The human genome contains many thousands of long noncoding RNAs (lncRNAs). While several studies have demonstrated compelling biological and disease roles for individual examples, analytical and experimental approaches to ...
  • Understanding transcriptional regulation by integrative analysis of transcription factor binding data
    Cheng, Chao; Alexander, Roger; Min, Renqiang; Leng, Jing; Yip, Kevin Y.; Rozowsky, Joel S.; Yan, Koon-Kiu; Dong, Xianjun; Djebali, Sarah; Ruan, Yijun; Davis, Carrie A.; Carninci, Piero; Lassmann, Timo; Gingeras, Thomas R.; Guigó Serra, Roderic; Birney, Ewan; Weng, Zhiping; Snyder, Michael; Gerstein, Mark B. (Cold Spring Harbor Laboratory Press (CSHL Press), 2012)
    Statistical models have been used to quantify the relationship between gene expression and transcription factor (TF) binding signals. Here we apply the models to the large-scale data generated by the ENCODE project to study ...

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