%0 Journal Article %1 Cesur:2018:Exp-Suppl:30535602 %A Cesur, M F %A Abdik, E %A Güven-Gülhan, Ü %A Durmuş, S %A Çakır, T %D 2018 %J Exp Suppl %K host-pathogen metabolic-networks %P 235-282 %R 10.1007/978-3-319-74932-7_6 %T Computational Systems Biology of Metabolism in Infection %U https://www.ncbi.nlm.nih.gov/pubmed/30535602 %V 109 %X A systems approach to elucidate the effect of infection on cell metabolism provides several opportunities from a better understanding of molecular mechanisms to the identification of potential biomarkers and drug targets. This is obvious from the fact that we have witnessed the accelerated use of computational systems biology in the last five years to study metabolic changes in pathogen and/or host cells in response to infection. In this chapter, we aim to present a comprehensive review of the recent research by focusing on genome-scale metabolic network models of pathogen-host systems and genome-wide metabolomics and fluxomics analysis of infected cells.

@article{Cesur:2018:Exp-Suppl:30535602, abstract = {A systems approach to elucidate the effect of infection on cell metabolism provides several opportunities from a better understanding of molecular mechanisms to the identification of potential biomarkers and drug targets. This is obvious from the fact that we have witnessed the accelerated use of computational systems biology in the last five years to study metabolic changes in pathogen and/or host cells in response to infection. In this chapter, we aim to present a comprehensive review of the recent research by focusing on genome-scale metabolic network models of pathogen-host systems and genome-wide metabolomics and fluxomics analysis of infected cells.}, added-at = {2018-12-22T04:14:46.000+0100}, author = {Cesur, M F and Abdik, E and G{\"u}ven-G{\"u}lhan, {\"U} and Durmuş, S and Çakır, T}, biburl = {https://www.bibsonomy.org/bibtex/274ce89185cc85690cdf22cfa73e3b048/karthikraman}, description = {Computational Systems Biology of Metabolism in Infection. - PubMed - NCBI}, doi = {10.1007/978-3-319-74932-7_6}, interhash = {62b79b596c1264c7a5bcf0bbda478bae}, intrahash = {74ce89185cc85690cdf22cfa73e3b048}, journal = {Exp Suppl}, keywords = {host-pathogen metabolic-networks}, pages = {235-282}, pmid = {30535602}, timestamp = {2018-12-22T04:15:11.000+0100}, title = {Computational Systems Biology of Metabolism in Infection}, url = {https://www.ncbi.nlm.nih.gov/pubmed/30535602}, volume = 109, year = 2018 }