| Title |
Networked buffering: a basic mechanism for distributed robustness in complex adaptive systems
|
|---|---|
| Published in |
Theoretical Biology and Medical Modelling, June 2010
|
| DOI | 10.1186/1742-4682-7-20 |
| Pubmed ID | |
| Authors |
James M Whitacre, Axel Bender |
| Abstract |
A generic mechanism--networked buffering--is proposed for the generation of robust traits in complex systems. It requires two basic conditions to be satisfied: 1) agents are versatile enough to perform more than one single functional role within a system and 2) agents are degenerate, i.e. there exists partial overlap in the functional capabilities of agents. Given these prerequisites, degenerate systems can readily produce a distributed systemic response to local perturbations. Reciprocally, excess resources related to a single function can indirectly support multiple unrelated functions within a degenerate system. In models of genome:proteome mappings for which localized decision-making and modularity of genetic functions are assumed, we verify that such distributed compensatory effects cause enhanced robustness of system traits. The conditions needed for networked buffering to occur are neither demanding nor rare, supporting the conjecture that degeneracy may fundamentally underpin distributed robustness within several biotic and abiotic systems. For instance, networked buffering offers new insights into systems engineering and planning activities that occur under high uncertainty. It may also help explain recent developments in understanding the origins of resilience within complex ecosystems. |
Mendeley readers
The data shown below were compiled from readership statistics for 90 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 3 | 3% |
| United States | 2 | 2% |
| Norway | 1 | 1% |
| Italy | 1 | 1% |
| Germany | 1 | 1% |
| Australia | 1 | 1% |
| Finland | 1 | 1% |
| Sweden | 1 | 1% |
| Netherlands | 1 | 1% |
| Other | 4 | 4% |
| Unknown | 74 | 82% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 23 | 26% |
| Student > Ph. D. Student | 22 | 24% |
| Student > Master | 9 | 10% |
| Student > Bachelor | 6 | 7% |
| Professor | 4 | 4% |
| Other | 18 | 20% |
| Unknown | 8 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 21 | 23% |
| Biochemistry, Genetics and Molecular Biology | 11 | 12% |
| Computer Science | 11 | 12% |
| Engineering | 6 | 7% |
| Environmental Science | 4 | 4% |
| Other | 24 | 27% |
| Unknown | 13 | 14% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 10 December 2021.
All research outputs
#7,413,245
of 22,663,969 outputs
Outputs from Theoretical Biology and Medical Modelling
#98
of 287 outputs
Outputs of similar age
#33,876
of 95,392 outputs
Outputs of similar age from Theoretical Biology and Medical Modelling
#2
of 4 outputs
Altmetric has tracked 22,663,969 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 287 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.4. This one has gotten more attention than average, scoring higher than 56% of its peers.
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We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.