↓ Skip to main content

Genotype-phenotype matching analysis of 38 Lactococcus lactisstrains using random forest methods

Overview of attention for article published in BMC Microbiology, March 2013
Altmetric Badge

Mentioned by

twitter
2 X users

Citations

dimensions_citation
30 Dimensions

Readers on

mendeley
55 Mendeley
Title
Genotype-phenotype matching analysis of 38 Lactococcus lactisstrains using random forest methods
Published in
BMC Microbiology, March 2013
DOI 10.1186/1471-2180-13-68
Pubmed ID
Authors

Jumamurat R Bayjanov, Marjo JC Starrenburg, Marijke R van der Sijde, Roland J Siezen, Sacha AFT van Hijum

Abstract

Lactococcus lactis is used in dairy food fermentation and for the efficient production of industrially relevant enzymes. The genome content and different phenotypes have been determined for multiple L. lactis strains in order to understand intra-species genotype and phenotype diversity and annotate gene functions. In this study, we identified relations between gene presence and a collection of 207 phenotypes across 38 L. lactis strains of dairy and plant origin. Gene occurrence and phenotype data were used in an iterative gene selection procedure, based on the Random Forest algorithm, to identify genotype-phenotype relations.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 2 4%
Sweden 1 2%
Kazakhstan 1 2%
Australia 1 2%
Unknown 50 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 25%
Student > Ph. D. Student 12 22%
Student > Master 8 15%
Other 4 7%
Student > Bachelor 4 7%
Other 6 11%
Unknown 7 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 22 40%
Biochemistry, Genetics and Molecular Biology 14 25%
Engineering 3 5%
Medicine and Dentistry 2 4%
Environmental Science 1 2%
Other 4 7%
Unknown 9 16%
Attention Score in Context

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 27 April 2013.
All research outputs
#15,267,294
of 22,703,044 outputs
Outputs from BMC Microbiology
#1,756
of 3,171 outputs
Outputs of similar age
#123,847
of 197,766 outputs
Outputs of similar age from BMC Microbiology
#22
of 33 outputs
Altmetric has tracked 22,703,044 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,171 research outputs from this source. They receive a mean Attention Score of 4.1. This one is in the 37th percentile – i.e., 37% 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 197,766 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 33 others from the same source and published within six weeks on either side of this one. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.