Chapter title |
Integrated Host-Pathogen Metabolic Reconstructions
|
---|---|
Chapter number | 9 |
Book title |
Metabolic Network Reconstruction and Modeling
|
Published in |
Methods in molecular biology, January 2018
|
DOI | 10.1007/978-1-4939-7528-0_9 |
Pubmed ID | |
Book ISBNs |
978-1-4939-7527-3, 978-1-4939-7528-0
|
Authors |
Anu Raghunathan, Neema Jamshidi |
Abstract |
The science and art of Genome scale metabolic network reconstructions have been explicitly documented in the literature for organisms across all the three kingdoms of life. Constraints-based models derived from such reconstructions have been used to assess metabolic phenotypes of their complex connections to genotype accurately. The problem of infectious disease is complex due to the multifactorial response of the host to the pathogen. Systems biology approaches and modeling allow one to study, understand, and predict emergent properties of such complex responses. The integration of the host and pathogen metabolic networks and the subsequent merger of their stoichiometric matrices is nontrivial and requires understanding of both pathogen and host metabolism and physiologies. The protocol here describes the detailed process of network and stoichiometric matrix merger using a salmonella-mouse macrophage model. The protocol also discusses the interfacial and objective functions required to actually embark on the analysis of host-pathogen interaction models. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 20 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 8 | 40% |
Researcher | 3 | 15% |
Student > Ph. D. Student | 2 | 10% |
Other | 2 | 10% |
Unspecified | 1 | 5% |
Other | 1 | 5% |
Unknown | 3 | 15% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 6 | 30% |
Biochemistry, Genetics and Molecular Biology | 4 | 20% |
Chemical Engineering | 1 | 5% |
Immunology and Microbiology | 1 | 5% |
Medicine and Dentistry | 1 | 5% |
Other | 1 | 5% |
Unknown | 6 | 30% |