↓ Skip to main content

Single-molecule dataset (SMD): a generalized storage format for raw and processed single-molecule data

Overview of attention for article published in BMC Bioinformatics, January 2015
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
3 tweeters

Citations

dimensions_citation
6 Dimensions

Readers on

mendeley
19 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Single-molecule dataset (SMD): a generalized storage format for raw and processed single-molecule data
Published in
BMC Bioinformatics, January 2015
DOI 10.1186/s12859-014-0429-4
Pubmed ID
Authors

Max Greenfeld, Jan-Willem van de Meent, Dmitri S Pavlichin, Hideo Mabuchi, Chris H Wiggins, Ruben L Gonzalez, Daniel Herschlag

Abstract

BackgroundSingle-molecule techniques have emerged as incisive approaches for addressing a wide range of questions arising in contemporary biological research [ 1-4]. The analysis and interpretation of raw single-molecule data benefits greatly from the ongoing development of sophisticated statistical analysis tools that enable accurate inference at the low signal-to-noise ratios frequently associated with these measurements. While a number of groups have released analysis toolkits as open source software [5-14], it remains difficult to compare analysis for experiments performed in different labs due to a lack of standardization.ResultsHere we propose a standardized single-molecule dataset (SMD) file format. SMD is designed to accommodate a wide variety of computer programming languages, single-molecule techniques, and analysis strategies. To facilitate adoption of this format we have made two existing data analysis packages that are used for single-molecule analysis compatible with this format.ConclusionAdoption of a common, standard data file format for sharing raw single-molecule data and analysis outcomes is a critical step for the emerging and powerful single-molecule field, which will benefit both sophisticated users and non-specialists by allowing standardized, transparent, and reproducible analysis practices.

Twitter Demographics

The data shown below were collected from the profiles of 3 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 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Switzerland 1 5%
United States 1 5%
Unknown 17 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 32%
Researcher 6 32%
Professor 2 11%
Other 1 5%
Student > Master 1 5%
Other 3 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 5 26%
Biochemistry, Genetics and Molecular Biology 4 21%
Computer Science 3 16%
Physics and Astronomy 3 16%
Chemistry 2 11%
Other 2 11%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 23 November 2018.
All research outputs
#8,371,190
of 13,906,652 outputs
Outputs from BMC Bioinformatics
#3,355
of 5,182 outputs
Outputs of similar age
#131,125
of 279,038 outputs
Outputs of similar age from BMC Bioinformatics
#24
of 43 outputs
Altmetric has tracked 13,906,652 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,182 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 31st percentile – i.e., 31% 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 279,038 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 43 others from the same source and published within six weeks on either side of this one. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.