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Fluidic Logic Used in a Systems Approach to Enable Integrated Single-Cell Functional Analysis

Overview of attention for article published in Frontiers in Bioengineering and Biotechnology, September 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (79th percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

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1 blog
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3 X users

Citations

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22 Dimensions

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45 Mendeley
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Title
Fluidic Logic Used in a Systems Approach to Enable Integrated Single-Cell Functional Analysis
Published in
Frontiers in Bioengineering and Biotechnology, September 2016
DOI 10.3389/fbioe.2016.00070
Pubmed ID
Authors

Naveen Ramalingam, Brian Fowler, Lukasz Szpankowski, Anne A. Leyrat, Kyle Hukari, Myo Thu Maung, Wiganda Yorza, Michael Norris, Chris Cesar, Joe Shuga, Michael L. Gonzales, Chad D. Sanada, Xiaohui Wang, Rudy Yeung, Win Hwang, Justin Axsom, Naga Sai Gopi Krishna Devaraju, Ninez Delos Angeles, Cassandra Greene, Ming-Fang Zhou, Eng-Seng Ong, Chang-Chee Poh, Marcos Lam, Henry Choi, Zaw Htoo, Leo Lee, Chee-Sing Chin, Zhong-Wei Shen, Chong T. Lu, Ilona Holcomb, Aik Ooi, Craig Stolarczyk, Tony Shuga, Kenneth J. Livak, Cate Larsen, Marc Unger, Jay A. A. West

Abstract

The study of single cells has evolved over the past several years to include expression and genomic analysis of an increasing number of single cells. Several studies have demonstrated wide spread variation and heterogeneity within cell populations of similar phenotype. While the characterization of these populations will likely set the foundation for our understanding of genomic- and expression-based diversity, it will not be able to link the functional differences of a single cell to its underlying genomic structure and activity. Currently, it is difficult to perturb single cells in a controlled environment, monitor and measure the response due to perturbation, and link these response measurements to downstream genomic and transcriptomic analysis. In order to address this challenge, we developed a platform to integrate and miniaturize many of the experimental steps required to study single-cell function. The heart of this platform is an elastomer-based integrated fluidic circuit that uses fluidic logic to select and sequester specific single cells based on a phenotypic trait for downstream experimentation. Experiments with sequestered cells that have been performed include on-chip culture, exposure to various stimulants, and post-exposure image-based response analysis, followed by preparation of the mRNA transcriptome for massively parallel sequencing analysis. The flexible system embodies experimental design and execution that enable routine functional studies of single cells.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Korea, Republic of 1 2%
United States 1 2%
Unknown 43 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 20%
Other 6 13%
Student > Ph. D. Student 6 13%
Student > Bachelor 4 9%
Professor > Associate Professor 4 9%
Other 8 18%
Unknown 8 18%
Readers by discipline Count As %
Engineering 10 22%
Agricultural and Biological Sciences 9 20%
Biochemistry, Genetics and Molecular Biology 7 16%
Nursing and Health Professions 2 4%
Chemistry 2 4%
Other 5 11%
Unknown 10 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 02 June 2017.
All research outputs
#3,935,065
of 22,889,074 outputs
Outputs from Frontiers in Bioengineering and Biotechnology
#527
of 6,643 outputs
Outputs of similar age
#65,434
of 320,659 outputs
Outputs of similar age from Frontiers in Bioengineering and Biotechnology
#2
of 18 outputs
Altmetric has tracked 22,889,074 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,643 research outputs from this source. They receive a mean Attention Score of 3.4. This one has done particularly well, scoring higher than 92% 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 320,659 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 79% of its contemporaries.
We're also able to compare this research output to 18 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.