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In-silico design of computational nucleic acids for molecular information processing

Overview of attention for article published in Journal of Cheminformatics, May 2013
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1 tweeter

Citations

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Title
In-silico design of computational nucleic acids for molecular information processing
Published in
Journal of Cheminformatics, May 2013
DOI 10.1186/1758-2946-5-22
Pubmed ID
Authors

Effirul Ikhwan Ramlan, Klaus-Peter Zauner

Abstract

Within recent years nucleic acids have become a focus of interest for prototype implementations of molecular computing concepts. During the same period the importance of ribonucleic acids as components of the regulatory networks within living cells has increasingly been revealed. Molecular computers are attractive due to their ability to function within a biological system; an application area extraneous to the present information technology paradigm. The existence of natural information processing architectures (predominately exemplified by protein) demonstrates that computing based on physical substrates that are radically different from silicon is feasible. Two key principles underlie molecular level information processing in organisms: conformational dynamics of macromolecules and self-assembly of macromolecules. Nucleic acids support both principles, and moreover computational design of these molecules is practicable. This study demonstrates the simplicity with which one can construct a set of nucleic acid computing units using a new computational protocol. With the new protocol, diverse classes of nucleic acids imitating the complete set of boolean logical operators were constructed. These nucleic acid classes display favourable thermodynamic properties and are significantly similar to the approximation of successful candidates implemented in the laboratory. This new protocol would enable the construction of a network of interconnecting nucleic acids (as a circuit) for molecular information processing.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 7%
Malaysia 1 7%
Chile 1 7%
Unknown 11 79%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 29%
Researcher 3 21%
Student > Bachelor 2 14%
Professor 1 7%
Professor > Associate Professor 1 7%
Other 0 0%
Unknown 3 21%
Readers by discipline Count As %
Agricultural and Biological Sciences 2 14%
Chemistry 2 14%
Biochemistry, Genetics and Molecular Biology 1 7%
Pharmacology, Toxicology and Pharmaceutical Science 1 7%
Psychology 1 7%
Other 3 21%
Unknown 4 29%

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 08 May 2013.
All research outputs
#3,074,314
of 4,507,280 outputs
Outputs from Journal of Cheminformatics
#209
of 253 outputs
Outputs of similar age
#60,205
of 88,881 outputs
Outputs of similar age from Journal of Cheminformatics
#10
of 12 outputs
Altmetric has tracked 4,507,280 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 253 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.1. This one is in the 4th percentile – i.e., 4% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 88,881 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 12 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.