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Record Nr. |
UNINA9910298323003321 |
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Autore |
Armitage Emily G |
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Titolo |
Correlation-based network analysis of cancer metabolism [[electronic resource] ] : A new systems biology approach in metabolomics / / by Emily G. Armitage, Helen L. Kotze, Kaye J. Williams |
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Pubbl/distr/stampa |
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New York, NY : , : Springer New York : , : Imprint : Springer, , 2014 |
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ISBN |
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Edizione |
[1st ed. 2014.] |
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Descrizione fisica |
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1 online resource (67 p.) |
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Collana |
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SpringerBriefs in Systems Biology, , 2193-4746 |
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Disciplina |
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Soggetti |
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Systems biology |
Metabolism |
Cancer research |
Systems Biology |
Metabolomics |
Cancer Research |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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An overview of Cancer metabolism -- Cancer hypoxia and the tumour microenvironment as effectors of cancer metabolism -- Metabolic fingerprinting of in vitro cancer cell samples -- Network-based correlation analysis of metabolic fingerprinting data -- Case study: Systems biology of HIF metabolism in cancer -- Case study: Systems biology of chemotherapy resistance in hypoxic cancer -- Index. |
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Sommario/riassunto |
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With the rise of systems biology as an approach in biochemistry research, using high throughput techniques such as mass spectrometry to generate metabolic profiles of cancer metabolism is becoming increasingly popular. There are examples of cancer metabolic profiling studies in the academic literature; however they are often only in journals specific to the metabolomics community. This book will be particularly useful for post-graduate students and post-doctoral researchers using this pioneering technique of network-based correlation analysis. The approach can be adapted to the analysis of any large scale metabolic profiling experiment to answer a range of biological questions in a range of species or for a range of diseases. |
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