2007
DOI: 10.1073/pnas.0701744104
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Functional information and the emergence of biocomplexity

Abstract: Complex emergent systems of many interacting components, including complex biological systems, have the potential to perform quantifiable functions. Accordingly, we define ''functional information,'' I(E x), as a measure of system complexity. For a given system and function, x (e.g., a folded RNA sequence that binds to GTP), and degree of function, E x (e.g., the RNA-GTP binding energy), I(E x) ‫؍‬ ؊log2[F(Ex)], where F(Ex) is the fraction of all possible configurations of the system that possess a degree of f… Show more

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Cited by 112 publications
(88 citation statements)
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References 53 publications
(57 reference statements)
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“…For example, Hazen et al (2007) propose a measure of "functional information". In general terms, a sequence of signs has higher functional information if it raises the probability of bringing about some predetermined outcome.…”
Section: The Quantitative Notion Of Informationmentioning
confidence: 99%
“…For example, Hazen et al (2007) propose a measure of "functional information". In general terms, a sequence of signs has higher functional information if it raises the probability of bringing about some predetermined outcome.…”
Section: The Quantitative Notion Of Informationmentioning
confidence: 99%
“…In chemical engineering, otherwise difficult design problems are made tractable by framing them as unit operations such that complex processes can be evaluated with coarsegrained models (Chau 2002). Biological systems exhibit functional complexity due to component interactions at many different scales, from individual protein and RNA subunits to genes, pathways, circuits and cells (Hazen et al 2007). In the absence of effective models and simulation tools, it remains difficult and resource intensive to engineer complex biological devices and systems (Keasling 2010).…”
Section: Progress Toward Design-driven Synthetic Biologymentioning
confidence: 99%
“…The successful development of our model-driven approach for engineering RNA devices relied upon the application of three generalizable strategies for managing biological complexity and enabling engineering tractability (Hazen et al 2007). First, a coarse-grained mechanistic model (Chau 2002), based on well-understood biochemistry (Deana et al 2008), was created to simulate device functions from measurable and tunable component characteristics.…”
Section: Progress Toward Design-driven Synthetic Biologymentioning
confidence: 99%
“…These exciting accomplishments left in their wake some more heretofore unconsidered questions, not all scientific, exposing newer horizons, which promise, in the most stunning manner, to usher a new dawn of scientific, technological, industrial, and regulatory endeavors, as discussed in the last section. Initial also because the signature of the next iteration can be distinctly identified from the first and is embodied in the collective effort to recapitulate the microenvironmental niche through the use of bioprinters, condensing laboratory into a computer and experiments into a code as part of the third approach, 150 employing the emergent 151,152 paradigm for understanding cellular behavior, and moving to an integrated approach to better understand, develop, and test TERM products. The TERM community stands at the edge of another transition with its horizon irrevocably broadened.…”
Section: New Frontiers and Future Directionsmentioning
confidence: 99%