Advanced methods and algorithms for biological networks analysis
Modeling and analysis of complex biological networks presents a number of mathematical challenges. For the models to be useful from a biological standpoint, they must be systematically compared with data. Robustness is a key to biological understanding and proper feedback to guide experiments, inclu...
| Main Authors: | , , , , |
|---|---|
| Format: | Journal article |
| Language: | English |
| Published: |
2006
|
| _version_ | 1797102982987251712 |
|---|---|
| author | El-Samad, H Prajna, S Papachristodoulou, A Doyle, J Khammash, M |
| author_facet | El-Samad, H Prajna, S Papachristodoulou, A Doyle, J Khammash, M |
| author_sort | El-Samad, H |
| collection | OXFORD |
| description | Modeling and analysis of complex biological networks presents a number of mathematical challenges. For the models to be useful from a biological standpoint, they must be systematically compared with data. Robustness is a key to biological understanding and proper feedback to guide experiments, including both the deterministic stability and performance properties of models in the presence of parametric uncertainties and their stochastic behavior in the presence of noise. In this paper, we present mathematical and algorithmic tools to address such questions for models that may be nonlinear, hybrid, and stochastic. These tools are rooted in solid mathematical theories, primarily from robust control and dynamical systems, but with important recent developments. They also have the potential for great practical relevance, which we explore through a series of biologically motivated examples. © 2006 IEEE. |
| first_indexed | 2024-03-07T06:13:33Z |
| format | Journal article |
| id | oxford-uuid:f0593978-a2e2-4c06-86f8-08b41b7db9b4 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T06:13:33Z |
| publishDate | 2006 |
| record_format | dspace |
| spelling | oxford-uuid:f0593978-a2e2-4c06-86f8-08b41b7db9b42022-03-27T11:47:09ZAdvanced methods and algorithms for biological networks analysisJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:f0593978-a2e2-4c06-86f8-08b41b7db9b4EnglishSymplectic Elements at Oxford2006El-Samad, HPrajna, SPapachristodoulou, ADoyle, JKhammash, MModeling and analysis of complex biological networks presents a number of mathematical challenges. For the models to be useful from a biological standpoint, they must be systematically compared with data. Robustness is a key to biological understanding and proper feedback to guide experiments, including both the deterministic stability and performance properties of models in the presence of parametric uncertainties and their stochastic behavior in the presence of noise. In this paper, we present mathematical and algorithmic tools to address such questions for models that may be nonlinear, hybrid, and stochastic. These tools are rooted in solid mathematical theories, primarily from robust control and dynamical systems, but with important recent developments. They also have the potential for great practical relevance, which we explore through a series of biologically motivated examples. © 2006 IEEE. |
| spellingShingle | El-Samad, H Prajna, S Papachristodoulou, A Doyle, J Khammash, M Advanced methods and algorithms for biological networks analysis |
| title | Advanced methods and algorithms for biological networks analysis |
| title_full | Advanced methods and algorithms for biological networks analysis |
| title_fullStr | Advanced methods and algorithms for biological networks analysis |
| title_full_unstemmed | Advanced methods and algorithms for biological networks analysis |
| title_short | Advanced methods and algorithms for biological networks analysis |
| title_sort | advanced methods and algorithms for biological networks analysis |
| work_keys_str_mv | AT elsamadh advancedmethodsandalgorithmsforbiologicalnetworksanalysis AT prajnas advancedmethodsandalgorithmsforbiologicalnetworksanalysis AT papachristodouloua advancedmethodsandalgorithmsforbiologicalnetworksanalysis AT doylej advancedmethodsandalgorithmsforbiologicalnetworksanalysis AT khammashm advancedmethodsandalgorithmsforbiologicalnetworksanalysis |