Generalized models for high-throughput analysis of uncertain nonlinear systems
Research output: Contribution to journal › Research article › Contributed › peer-review
Contributors
Abstract
Purpose: Describe a high-throughput method for the analysis of uncertain models, e. g. in biological research. Methods: Generalized modeling for conceptual analysis of large classes of models. Results: Local dynamics of uncertain networks are revealed as a function of intuitive parameters. Conclusions: Generalized modeling easily scales to very large networks.
Details
| Original language | English |
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| Article number | 9 |
| Pages (from-to) | 1-4 |
| Number of pages | 4 |
| Journal | Journal of Mathematics in Industry |
| Volume | 1 |
| Issue number | 1 |
| Publication status | Published - 2011 |
| Peer-reviewed | Yes |
External IDs
| ORCID | /0000-0003-0967-6747/work/149795413 |
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Keywords
ASJC Scopus subject areas
Keywords
- biological research, Generalized modeling, high-throughput method, uncertain models