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A cargo-sorting DNA robot

Overview of attention for article published in Science, September 2017
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

Mentioned by

news
41 news outlets
blogs
13 blogs
twitter
174 tweeters
facebook
8 Facebook pages
wikipedia
1 Wikipedia page
googleplus
6 Google+ users
video
1 video uploader

Citations

dimensions_citation
62 Dimensions

Readers on

mendeley
214 Mendeley
Title
A cargo-sorting DNA robot
Published in
Science, September 2017
DOI 10.1126/science.aan6558
Pubmed ID
Authors

Anupama J. Thubagere, Wei Li, Robert F. Johnson, Zibo Chen, Shayan Doroudi, Yae Lim Lee, Gregory Izatt, Sarah Wittman, Niranjan Srinivas, Damien Woods, Erik Winfree, Lulu Qian

Abstract

Two critical challenges in the design and synthesis of molecular robots are modularity and algorithm simplicity. We demonstrate three modular building blocks for a DNA robot that performs cargo sorting at the molecular level. A simple algorithm encoding recognition between cargos and their destinations allows for a simple robot design: a single-stranded DNA with one leg and two foot domains for walking, and one arm and one hand domain for picking up and dropping off cargos. The robot explores a two-dimensional testing ground on the surface of DNA origami, picks up multiple cargos of two types that are initially at unordered locations, and delivers them to specified destinations until all molecules are sorted into two distinct piles. The robot is designed to perform a random walk without any energy supply. Exploiting this feature, a single robot can repeatedly sort multiple cargos. Localization on DNA origami allows for distinct cargo-sorting tasks to take place simultaneously in one test tube or for multiple robots to collectively perform the same task.

Twitter Demographics

The data shown below were collected from the profiles of 174 tweeters 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 214 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 214 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 57 27%
Researcher 38 18%
Student > Bachelor 35 16%
Student > Master 28 13%
Unspecified 17 8%
Other 39 18%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 44 21%
Agricultural and Biological Sciences 42 20%
Chemistry 39 18%
Engineering 22 10%
Unspecified 22 10%
Other 45 21%

Attention Score in Context

This research output has an Altmetric Attention Score of 511. 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 15 February 2019.
All research outputs
#13,906
of 12,693,765 outputs
Outputs from Science
#778
of 59,676 outputs
Outputs of similar age
#768
of 265,727 outputs
Outputs of similar age from Science
#45
of 957 outputs
Altmetric has tracked 12,693,765 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 59,676 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 41.0. This one has done particularly well, scoring higher than 98% of its peers.
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 265,727 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 957 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.