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Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass-Spectrometry (MALDI-TOF MS) Based Microbial Identifications: Challenges and Scopes for Microbial Ecologists

Overview of attention for article published in Frontiers in Microbiology, August 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)
  • High Attention Score compared to outputs of the same age and source (82nd percentile)

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1 blog
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4 X users
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1 Google+ user

Citations

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212 Mendeley
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Title
Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass-Spectrometry (MALDI-TOF MS) Based Microbial Identifications: Challenges and Scopes for Microbial Ecologists
Published in
Frontiers in Microbiology, August 2016
DOI 10.3389/fmicb.2016.01359
Pubmed ID
Authors

Praveen Rahi, Om Prakash, Yogesh S. Shouche

Abstract

Matrix-assisted laser desorption/ionization time-of-flight mass-spectrometry (MALDI-TOF MS) based biotyping is an emerging technique for high-throughput and rapid microbial identification. Due to its relatively higher accuracy, comprehensive database of clinically important microorganisms and low-cost compared to other microbial identification methods, MALDI-TOF MS has started replacing existing practices prevalent in clinical diagnosis. However, applicability of MALDI-TOF MS in the area of microbial ecology research is still limited mainly due to the lack of data on non-clinical microorganisms. Intense research activities on cultivation of microbial diversity by conventional as well as by innovative and high-throughput methods has substantially increased the number of microbial species known today. This important area of research is in urgent need of rapid and reliable method(s) for characterization and de-replication of microorganisms from various ecosystems. MALDI-TOF MS based characterization, in our opinion, appears to be the most suitable technique for such studies. Reliability of MALDI-TOF MS based identification method depends mainly on accuracy and width of reference databases, which need continuous expansion and improvement. In this review, we propose a common strategy to generate MALDI-TOF MS spectral database and advocated its sharing, and also discuss the role of MALDI-TOF MS based high-throughput microbial identification in microbial ecology studies.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 212 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
India 1 <1%
Germany 1 <1%
Canada 1 <1%
Unknown 209 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 34 16%
Student > Master 32 15%
Student > Ph. D. Student 30 14%
Student > Bachelor 20 9%
Student > Doctoral Student 19 9%
Other 31 15%
Unknown 46 22%
Readers by discipline Count As %
Agricultural and Biological Sciences 41 19%
Biochemistry, Genetics and Molecular Biology 38 18%
Immunology and Microbiology 25 12%
Chemistry 15 7%
Environmental Science 7 3%
Other 31 15%
Unknown 55 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 16 October 2016.
All research outputs
#3,067,964
of 22,883,326 outputs
Outputs from Frontiers in Microbiology
#2,762
of 24,918 outputs
Outputs of similar age
#54,922
of 336,888 outputs
Outputs of similar age from Frontiers in Microbiology
#73
of 423 outputs
Altmetric has tracked 22,883,326 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 24,918 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.3. This one has done well, scoring higher than 88% 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 336,888 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 83% of its contemporaries.
We're also able to compare this research output to 423 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.