dorsal/arxiv
View SchemaThe Role of Computation in Complex Regulatory Networks
| Authors | Pau Fernandez, Ricard V. Sole |
|---|---|
| Categories | |
| ArXiv ID | q-bio/0311012 |
| URL | https://arxiv.org/abs/q-bio/0311012 |
Abstract
Biological phenomena differ significantly from physical phenomena. At the heart of this distinction is the fact that biological entities have computational abilities and thus they are inherently difficult to predict. This is the reason why simplified models that provide the minimal requirements for computation turn out to be very useful to study networks of many components. In this chapter, we briefly review the dynamical aspects of models of regulatory networks, discussing their most salient features, and we also show how these models can give clues about the way in which networks may organize their capacity to evolve, by providing simple examples of the implementation of robustness and modularity.
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"abstract": "Biological phenomena differ significantly from physical phenomena. At the\nheart of this distinction is the fact that biological entities have\ncomputational abilities and thus they are inherently difficult to predict. This\nis the reason why simplified models that provide the minimal requirements for\ncomputation turn out to be very useful to study networks of many components. In\nthis chapter, we briefly review the dynamical aspects of models of regulatory\nnetworks, discussing their most salient features, and we also show how these\nmodels can give clues about the way in which networks may organize their\ncapacity to evolve, by providing simple examples of the implementation of\nrobustness and modularity.",
"arxiv_id": "q-bio/0311012",
"authors": [
"Pau Fernandez",
"Ricard V. Sole"
],
"categories": [
"q-bio.MN",
"q-bio.GN",
"q-bio.PE"
],
"title": "The Role of Computation in Complex Regulatory Networks",
"url": "https://arxiv.org/abs/q-bio/0311012"
},
"schema_id": "dorsal/arxiv",
"source": {
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"type": "Model",
"variant": "snapshot-2026-03-01",
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