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Expression-based reverse engineering of plant transcriptional networks: A practical study on the interpretation of Next Generation Sequencing and Microarray data in plants - Brossura
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Regulation of gene transcription plays a major role in mediating cellular responses and physiological behavior in all known organisms. The finding that similar genes are often regulated in a similar manner (co-regulated or "co-expressed") has directed several "guilt-by-association" approaches in order to reverse-engineer the cellular transcriptional networks using gene expression data as a compass. This kind of studies has been considerably assisted in the recent years by the development of high-throughput transcript measurement platforms, specifically gene microarrays and next-generation sequencing. In this work, several approaches are described for improving the extraction and interpretation of the information contained in plant transcriptional data, obtained from microarrays or through next generation sequencing. Applications of these theoretical approaches, ranging from Pearson correlation to LASSO and hybrid methods, are described for the reverse engineering of tuber growth transcriptional networks, for the prediction of essential genes and in the task of defining the full transcriptome of the extremophile plant Thellungiella salsuginea.
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L'autore
Dr. Federico Manuel Giorgi studied experimental Biotechnology in Bologna and Amsterdam between 2001 and 2006. He then specialized in Bioinformatics, first studying the network properties of cancer genes in Milan (IEO), then focusing on plant transcriptional networks in Golm (MPI). He is now working on plant genomes in Udine (IGA).
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Expression-based reverse engineering of plant transcriptional networks
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LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3846584649
ISBN 13: 9783846584644
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Kartoniert / Broschiert. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Giorgi FedericoDr. Federico Manuel Giorgi studied experimental Biotechnology in Bologna and Amsterdam between 2001 and 2006. He then specialized in Bioinformatics, first studying the network properties of cancer genes in Milan (IEO),. Codice articolo 5501321
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Expression-based reverse engineering of plant transcriptional networks
Editore:
LAP Lambert Academic Publishing, 2012
ISBN 10: 3846584649
ISBN 13: 9783846584644
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Regulation of gene transcription plays a major role in mediating cellular responses and physiological behavior in all known organisms. The finding that similar genes are often regulated in a similar manner (co-regulated or 'co-expressed') has directed several 'guilt-by-association' approaches in order to reverse-engineer the cellular transcriptional networks using gene expression data as a compass. This kind of studies has been considerably assisted in the recent years by the development of high-throughput transcript measurement platforms, specifically gene microarrays and next-generation sequencing. In this work, several approaches are described for improving the extraction and interpretation of the information contained in plant transcriptional data, obtained from microarrays or through next generation sequencing. Applications of these theoretical approaches, ranging from Pearson correlation to LASSO and hybrid methods, are described for the reverse engineering of tuber growth transcriptional networks, for the prediction of essential genes and in the task of defining the full transcriptome of the extremophile plant Thellungiella salsuginea. 156 pp. Englisch. Codice articolo 9783846584644
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Expression-based reverse engineering of plant transcriptional networks : A practical study on the interpretation of Next Generation Sequencing and Microarray data in plants
Editore:
LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3846584649
ISBN 13: 9783846584644
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Da: AHA-BUCH GmbH, Einbeck, Germania
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Regulation of gene transcription plays a major role in mediating cellular responses and physiological behavior in all known organisms. The finding that similar genes are often regulated in a similar manner (co-regulated or 'co-expressed') has directed several 'guilt-by-association' approaches in order to reverse-engineer the cellular transcriptional networks using gene expression data as a compass. This kind of studies has been considerably assisted in the recent years by the development of high-throughput transcript measurement platforms, specifically gene microarrays and next-generation sequencing. In this work, several approaches are described for improving the extraction and interpretation of the information contained in plant transcriptional data, obtained from microarrays or through next generation sequencing. Applications of these theoretical approaches, ranging from Pearson correlation to LASSO and hybrid methods, are described for the reverse engineering of tuber growth transcriptional networks, for the prediction of essential genes and in the task of defining the full transcriptome of the extremophile plant Thellungiella salsuginea. Codice articolo 9783846584644
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Expression-based reverse engineering of plant transcriptional networks
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LAP LAMBERT Academic Publishing Jan 2012, 2012
ISBN 10: 3846584649
ISBN 13: 9783846584644
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Regulation of gene transcription plays a major role in mediating cellular responses and physiological behavior in all known organisms. The finding that similar genes are often regulated in a similar manner (co-regulated or 'co-expressed') has directed several 'guilt-by-association' approaches in order to reverse-engineer the cellular transcriptional networks using gene expression data as a compass. This kind of studies has been considerably assisted in the recent years by the development of high-throughput transcript measurement platforms, specifically gene microarrays and next-generation sequencing. In this work, several approaches are described for improving the extraction and interpretation of the information contained in plant transcriptional data, obtained from microarrays or through next generation sequencing. Applications of these theoretical approaches, ranging from Pearson correlation to LASSO and hybrid methods, are described for the reverse engineering of tuber growth transcriptional networks, for the prediction of essential genes and in the task of defining the full transcriptome of the extremophile plant Thellungiella salsuginea.Books on Demand GmbH, Überseering 33, 22297 Hamburg 156 pp. Englisch. Codice articolo 9783846584644
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