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Systematic Biological Filter Design with a Desired IO Filtering Response Based on Promoter-RBS Libraries

Overview of attention for article published in IEEE/ACM Transactions on Computational Biology and Bioinformatics, January 2014
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Article details
Title
Systematic Biological Filter Design with a Desired IO Filtering Response Based on Promoter-RBS Libraries
Published in
IEEE/ACM Transactions on Computational Biology and Bioinformatics, January 2014
DOI 10.1109/tcbb.2014.2372790
Pubmed ID
Authors
Abstract

In this study, robust biological filters with an external control to match a desired input/output (I/O) filtering response are engineered based on the well-characterized promoter-RBS libraries and a cascade gene circuit topology. In the field of synthetic biology, the biological filter system serves as a powerful detector or sensor to sense different molecular signals and produces a specific output response only if the concentration of the input molecular signal is higher or lower than a specified threshold. The proposed systematic design method of robust biological filters is summarized into three steps. Firstly, several well-characterized promoter-RBS libraries are established for biological filter design by identifying and collecting the quantitative and qualitative characteristics of their promoter-RBS components via nonlinear parameter estimation method. Then, the topology of synthetic biological filter is decomposed into three cascade gene regulatory modules, and an appropriate promoter-RBS library is selected for each module to achieve the desired I/O specification of a biological filter. Finally, based on the proposed systematic method, a robust externally tunable biological filter is engineered by searching the promoter-RBS component libraries and a control inducer concentration library to achieve the optimal reference match for the specified I/O filtering response.

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Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Bachelor 2 33%
Professor > Associate Professor 1 17%
Lecturer 1 17%
Student > Master 1 17%
Unknown 1 17%
Readers by discipline
Readers by discipline Count As %
Agricultural and Biological Sciences 1 17%
Sports and Recreations 1 17%
Social Sciences 1 17%
Engineering 1 17%
Design 1 17%
Other 0 0%
Unknown 1 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 12 September 2015.
All research outputs
#20,657,128
of 25,377,790 outputs
Outputs from IEEE/ACM Transactions on Computational Biology and Bioinformatics
#671
of 1,081 outputs
Outputs of similar age
#243,512
of 321,154 outputs
Outputs of similar age from IEEE/ACM Transactions on Computational Biology and Bioinformatics
#19
of 29 outputs
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So far Altmetric has tracked 1,081 research outputs from this source. They receive a mean Attention Score of 2.4. This one is in the 24th percentile – i.e., 24% of its peers scored the same or lower than it.
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