RNA-Seq provides an ideal platform to study the complete set of transcripts for a specific developmental stage or physiological condition. It reveals not only expression-level changes, but also structural changes in the coding sequences, including gene rearrangements. In this dissertation, I present my contributions to the development of computational tools for the robust and efficient analysis of RNA-Seq data to support cancer research. To automate the laborious and computationally intensive procedure of RNA-Seq data management, I worked on the development of Hydra, an RNA-Seq pipeline for the parallel processing and quality control of large numbers of samples. I then present QueryFuse, a novel gene-specific fusion-detection algorithm for aligned RNA-Seq data. It is designed to help biologists find and/or computationally validate fusions of interest quickly, and to annotate the detected events with visualization and detailed properties of the supporting reads. Finally, I contributed to the identification of a novel fusion event in lymphoma, with potential therapeutic implications in clinical samples. I validated this fusion in silico and by experimental validation.
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -RNA-Seq provides an ideal platform to study the complete set of transcripts for a specific developmental stage or physiological condition. It reveals not only expression-level changes, but also structural changes in the coding sequences, including gene rearrangements. In this dissertation, I present my contributions to the development of computational tools for the robust and efficient analysis of RNA-Seq data to support cancer research. To automate the laborious and computationally intensive procedure of RNA-Seq data management, I worked on the development of Hydra, an RNA-Seq pipeline for the parallel processing and quality control of large numbers of samples. I then present QueryFuse, a novel gene-specific fusion-detection algorithm for aligned RNA-Seq data. It is designed to help biologists find and/or computationally validate fusions of interest quickly, and to annotate the detected events with visualization and detailed properties of the supporting reads. Finally, I contributed to the identification of a novel fusion event in lymphoma, with potential therapeutic implications in clinical samples. I validated this fusion in silico and by experimental validation. 108 pp. Englisch. Codice articolo 9783659870873
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Da: Books Puddle, New York, NY, U.S.A.
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Da: moluna, Greven, Germania
Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Tan YuxiangCurrent:Post-doctoral fellowship, Bio-medical Transnational Research Institute of Jinan University, ChinaPh.D., Bioinformatics, Boston University School of Medicine, Boston,Research interest: Computational applications in . Codice articolo 159146715
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Da: Biblios, Frankfurt am main, HESSE, Germania
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Paperback. Condizione: Brand New. 108 pages. 8.66x5.91x0.25 inches. In Stock. Codice articolo 3659870870
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -RNA-Seq provides an ideal platform to study the complete set of transcripts for a specific developmental stage or physiological condition. It reveals not only expression-level changes, but also structural changes in the coding sequences, including gene rearrangements. In this dissertation, I present my contributions to the development of computational tools for the robust and efficient analysis of RNA-Seq data to support cancer research. To automate the laborious and computationally intensive procedure of RNA-Seq data management, I worked on the development of Hydra, an RNA-Seq pipeline for the parallel processing and quality control of large numbers of samples. I then present QueryFuse, a novel gene-specific fusion-detection algorithm for aligned RNA-Seq data. It is designed to help biologists find and/or computationally validate fusions of interest quickly, and to annotate the detected events with visualization and detailed properties of the supporting reads. Finally, I contributed to the identification of a novel fusion event in lymphoma, with potential therapeutic implications in clinical samples. I validated this fusion in silico and by experimental validation.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 108 pp. Englisch. Codice articolo 9783659870873
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Da: AHA-BUCH GmbH, Einbeck, Germania
Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - RNA-Seq provides an ideal platform to study the complete set of transcripts for a specific developmental stage or physiological condition. It reveals not only expression-level changes, but also structural changes in the coding sequences, including gene rearrangements. In this dissertation, I present my contributions to the development of computational tools for the robust and efficient analysis of RNA-Seq data to support cancer research. To automate the laborious and computationally intensive procedure of RNA-Seq data management, I worked on the development of Hydra, an RNA-Seq pipeline for the parallel processing and quality control of large numbers of samples. I then present QueryFuse, a novel gene-specific fusion-detection algorithm for aligned RNA-Seq data. It is designed to help biologists find and/or computationally validate fusions of interest quickly, and to annotate the detected events with visualization and detailed properties of the supporting reads. Finally, I contributed to the identification of a novel fusion event in lymphoma, with potential therapeutic implications in clinical samples. I validated this fusion in silico and by experimental validation. Codice articolo 9783659870873
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Da: preigu, Osnabrück, Germania
Taschenbuch. Condizione: Neu. Computational Approaches for Transcriptome Cancer Analysis by RNA-Seq | Yuxiang Tan | Taschenbuch | 108 S. | Englisch | 2016 | LAP LAMBERT Academic Publishing | EAN 9783659870873 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Codice articolo 103670650
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