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Genome-Wide Prediction and Analysis of Protein-Protein Functional Linkages in Bacteria [electronic resource] / by Vijaykumar Yogesh Muley, Vishal Acharya.

By: Muley, Vijaykumar Yogesh [author.].
Contributor(s): Acharya, Vishal [author.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: SpringerBriefs in Systems Biology: 2Publisher: New York, NY : Springer New York : Imprint: Springer, 2013Description: X, 60 p. 19 illus., 12 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9781461447054.Subject(s): Life sciences | Human genetics | Proteomics | Bioinformatics | Biological models | Life Sciences | Systems Biology | Bioinformatics | Human Genetics | ProteomicsDDC classification: 570 Online resources: Click here to access online
Contents:
Introduction -- From genomes to protein functions -- Co-evolutionary signals within genome sequences reflect functional dependence of proteins -- Chromosomal proximity of genes as an indicator of functional linkage -- Analyses of complex genome-scale biological networks -- Applications of protein interaction networks.
In: Springer eBooksSummary: Using genome sequencing, one can predict possible interactions among proteins. There are very few titles that focus on protein-protein interaction predictions in bacteria. The authors will describe these methods and further highlight its use to predict various biological pathways and complexity of the cellular response to various environmental conditions. Topics include analysis of complex genome-scale protein-protein interaction networks, effects of reference genome selection on prediction accuracy, and genome sequence templates to predict protein function.
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Introduction -- From genomes to protein functions -- Co-evolutionary signals within genome sequences reflect functional dependence of proteins -- Chromosomal proximity of genes as an indicator of functional linkage -- Analyses of complex genome-scale biological networks -- Applications of protein interaction networks.

Using genome sequencing, one can predict possible interactions among proteins. There are very few titles that focus on protein-protein interaction predictions in bacteria. The authors will describe these methods and further highlight its use to predict various biological pathways and complexity of the cellular response to various environmental conditions. Topics include analysis of complex genome-scale protein-protein interaction networks, effects of reference genome selection on prediction accuracy, and genome sequence templates to predict protein function.

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