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How to Make a Synthetic Multicellular Computer

Overview of attention for article published in PLOS ONE, February 2014
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Title
How to Make a Synthetic Multicellular Computer
Published in
PLOS ONE, February 2014
DOI 10.1371/journal.pone.0081248
Pubmed ID
Authors

Javier Macia, Ricard Sole

Abstract

Biological systems perform computations at multiple scales and they do so in a robust way. Engineering metaphors have often been used in order to provide a rationale for modeling cellular and molecular computing networks and as the basis for their synthetic design. However, a major constraint in this mapping between electronic and wet computational circuits is the wiring problem. Although wires are identical within electronic devices, they must be different when using synthetic biology designs. Moreover, in most cases the designed molecular systems cannot be reused for other functions. A new approximation allows us to simplify the problem by using synthetic cellular consortia where the output of the computation is distributed over multiple engineered cells. By evolving circuits in silico, we can obtain the minimal sets of Boolean units required to solve the given problem at the lowest cost using cellular consortia. Our analysis reveals that the basic set of logic units is typically non-standard. Among the most common units, the so called inverted IMPLIES (N-Implies) appears to be one of the most important elements along with the NOT and AND functions. Although NOR and NAND gates are widely used in electronics, evolved circuits based on combinations of these gates are rare, thus suggesting that the strategy of combining the same basic logic gates might be inappropriate in order to easily implement synthetic computational constructs. The implications for future synthetic designs, the general view of synthetic biology as a standard engineering domain, as well as potencial drawbacks are outlined.

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Mendeley readers

The data shown below were compiled from readership statistics for 138 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 5 4%
United Kingdom 2 1%
Portugal 1 <1%
Mexico 1 <1%
Vietnam 1 <1%
China 1 <1%
Luxembourg 1 <1%
Unknown 126 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 41 30%
Researcher 20 14%
Student > Master 16 12%
Student > Bachelor 14 10%
Professor 7 5%
Other 26 19%
Unknown 14 10%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 35 25%
Agricultural and Biological Sciences 34 25%
Engineering 17 12%
Computer Science 10 7%
Chemistry 5 4%
Other 19 14%
Unknown 18 13%