Search Results - "Wan, Yuk Kei"

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    Extensible combinatorial CRISPR screening in mammalian cells by Zhou, Peng, Wan, Yuk Kei, Chan, Becky K.C., Choi, Gigi C.G., Wong, Alan S.L.

    Published in STAR protocols (19-03-2021)
    “…The CRISPR-Cas system coupled with Combinatorial Genetics En Masse (CombiGEM) enables systematic analysis of high-order genetic perturbations that are…”
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    Beyond sequencing: machine learning algorithms extract biology hidden in Nanopore signal data by Wan, Yuk Kei, Hendra, Christopher, Pratanwanich, Ploy N., Göke, Jonathan

    Published in Trends in genetics (01-03-2022)
    “…Nanopore sequencing provides signal data corresponding to the nucleotide motifs sequenced. Through machine learning-based methods, these signals are translated…”
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    Detection of m6A from direct RNA sequencing using a multiple instance learning framework by Hendra, Christopher, Pratanwanich, Ploy N., Wan, Yuk Kei, Goh, W. S. Sho, Thiery, Alexandre, Göke, Jonathan

    Published in Nature methods (01-12-2022)
    “…RNA modifications such as m6A methylation form an additional layer of complexity in the transcriptome. Nanopore direct RNA sequencing can capture this…”
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    Context-aware transcript quantification from long-read RNA-seq data with Bambu by Chen, Ying, Sim, Andre, Wan, Yuk Kei, Yeo, Keith, Lee, Joseph Jing Xian, Ling, Min Hao, Love, Michael I., Göke, Jonathan

    Published in Nature methods (01-08-2023)
    “…Most approaches to transcript quantification rely on fixed reference annotations; however, the transcriptome is dynamic and depending on the context, such…”
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    Identification of differential RNA modifications from nanopore direct RNA sequencing with xPore by Pratanwanich, Ploy N., Yao, Fei, Chen, Ying, Koh, Casslynn W. Q., Wan, Yuk Kei, Hendra, Christopher, Poon, Polly, Goh, Yeek Teck, Yap, Phoebe M. L., Chooi, Jing Yuan, Chng, Wee Joo, Ng, Sarah B., Thiery, Alexandre, Goh, W. S. Sho, Göke, Jonathan

    Published in Nature biotechnology (01-11-2021)
    “…RNA modifications, such as N 6 -methyladenosine (m 6 A), modulate functions of cellular RNA species. However, quantifying differences in RNA modifications has…”
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    Systematic assessment of long-read RNA-seq methods for transcript identification and quantification by Pardo-Palacios, Francisco J., Wang, Dingjie, Reese, Fairlie, Diekhans, Mark, Carbonell-Sala, Sílvia, Williams, Brian, Loveland, Jane E., De María, Maite, Adams, Matthew S., Balderrama-Gutierrez, Gabriela, Behera, Amit K., Gonzalez Martinez, Jose M., Hunt, Toby, Lagarde, Julien, Liang, Cindy E., Li, Haoran, Meade, Marcus Jerryd, Moraga Amador, David A., Prjibelski, Andrey D., Birol, Inanc, Bostan, Hamed, Brooks, Ashley M., Çelik, Muhammed Hasan, Chen, Ying, Du, Mei R. M., Felton, Colette, Göke, Jonathan, Hafezqorani, Saber, Herwig, Ralf, Kawaji, Hideya, Lee, Joseph, Li, Jian-Liang, Lienhard, Matthias, Mikheenko, Alla, Mulligan, Dennis, Nip, Ka Ming, Pertea, Mihaela, Ritchie, Matthew E., Sim, Andre D., Tang, Alison D., Wan, Yuk Kei, Wang, Changqing, Wong, Brandon Y., Yang, Chen, Barnes, If, Berry, Andrew E., Capella-Gutierrez, Salvador, Cousineau, Alyssa, Dhillon, Namrita, Fernandez-Gonzalez, Jose M., Ferrández-Peral, Luis, Garcia-Reyero, Natàlia, Götz, Stefan, Hernández-Ferrer, Carles, Kondratova, Liudmyla, Liu, Tianyuan, Martinez-Martin, Alessandra, Menor, Carlos, Mestre-Tomás, Jorge, Mudge, Jonathan M., Panayotova, Nedka G., Paniagua, Alejandro, Repchevsky, Dmitry, Ren, Xingjie, Rouchka, Eric, Saint-John, Brandon, Sapena, Enrique, Sheynkman, Leon, Smith, Melissa Laird, Suner, Marie-Marthe, Takahashi, Hazuki, Youngworth, Ingrid A., Carninci, Piero, Denslow, Nancy D., Guigó, Roderic, Hunter, Margaret E., Maehr, Rene, Shen, Yin, Tilgner, Hagen U., Wold, Barbara J., Vollmers, Christopher, Frankish, Adam, Au, Kin Fai, Sheynkman, Gloria M., Mortazavi, Ali, Conesa, Ana, Brooks, Angela N.

    Published in Nature methods (01-07-2024)
    “…The Long-read RNA-Seq Genome Annotation Assessment Project Consortium was formed to evaluate the effectiveness of long-read approaches for transcriptome…”
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    High-Throughput Protein Engineering by Massively Parallel Combinatorial Mutagenesis by Wan, Yuk Kei, Choi, Gigi C G, Wong, Alan S L

    “…Exploring how combinatorial mutations can be combined to optimize protein functions is important to guide protein engineering. Given the vast combinatorial…”
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