| Chapter title |
Modeling Procedures
|
|---|---|
| Chapter number | 2 |
| Book title |
Modeling Methods for Medical Systems Biology
|
| Published in |
Advances in experimental medicine and biology, August 2018
|
| DOI | 10.1007/978-3-319-89354-9_2 |
| Pubmed ID | |
| Book ISBNs |
978-3-31-989353-2, 978-3-31-989354-9
|
| Authors |
María Elena Álvarez-Buylla Roces, Juan Carlos Martínez-García, José Dávila-Velderrain, Elisa Domínguez-Hüttinger, Mariana Esther Martínez-Sánchez, Álvarez-Buylla Roces, María Elena, Martínez-García, Juan Carlos, Dávila-Velderrain, José, Domínguez-Hüttinger, Elisa, Martínez-Sánchez, Mariana Esther |
| Abstract |
Being concerned by the understanding of the mechanism underlying chronic degenerative diseases , we presented in the previous chapter the medical systems biology conceptual framework that we present for that purpose in this volume. More specifically, we argued there the clear advantages offered by a state-space perspective when applied to the systems-level description of the biomolecular machinery that regulates complex degenerative diseases. We also discussed the importance of the dynamical interplay between the risk factors and the network of interdependencies that characterizes the biochemical, cellular, and tissue-level biomolecular reactions that underlie the physiological processes in health and disease. As we pointed out in the previous chapter, the understanding of this interplay (articulated around cellular phenotypic plasticity properties, regulated by specific kinds of gene regulatory networks) is necessary if prevention is chosen as the human-health improvement strategy (potentially involving the modulation of the patient's lifestyle). In this chapter we provide the medical systems biology mathematical and computational modeling tools required for this task. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 18 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 2 | 11% |
| Researcher | 2 | 11% |
| Student > Ph. D. Student | 2 | 11% |
| Librarian | 1 | 6% |
| Student > Master | 1 | 6% |
| Other | 1 | 6% |
| Unknown | 9 | 50% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 3 | 17% |
| Biochemistry, Genetics and Molecular Biology | 2 | 11% |
| Mathematics | 1 | 6% |
| Agricultural and Biological Sciences | 1 | 6% |
| Nursing and Health Professions | 1 | 6% |
| Other | 0 | 0% |
| Unknown | 10 | 56% |