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Ribosome signatures aid bacterial translation initiation site identification

Overview of attention for article published in BMC Biology, August 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (71st percentile)

Mentioned by

9 tweeters


22 Dimensions

Readers on

40 Mendeley
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Ribosome signatures aid bacterial translation initiation site identification
Published in
BMC Biology, August 2017
DOI 10.1186/s12915-017-0416-0
Pubmed ID

Adam Giess, Veronique Jonckheere, Elvis Ndah, Katarzyna Chyżyńska, Petra Van Damme, Eivind Valen


While methods for annotation of genes are increasingly reliable, the exact identification of translation initiation sites remains a challenging problem. Since the N-termini of proteins often contain regulatory and targeting information, developing a robust method for start site identification is crucial. Ribosome profiling reads show distinct patterns of read length distributions around translation initiation sites. These patterns are typically lost in standard ribosome profiling analysis pipelines, when reads from footprints are adjusted to determine the specific codon being translated. Utilising these signatures in combination with nucleotide sequence information, we build a model capable of predicting translation initiation sites and demonstrate its high accuracy using N-terminal proteomics. Applying this to prokaryotic translatomes, we re-annotate translation initiation sites and provide evidence of N-terminal truncations and extensions of previously annotated coding sequences. These re-annotations are supported by the presence of structural and sequence-based features next to N-terminal peptide evidence. Finally, our model identifies 61 novel genes previously undiscovered in the Salmonella enterica genome. Signatures within ribosome profiling read length distributions can be used in combination with nucleotide sequence information to provide accurate genome-wide identification of translation initiation sites.

Twitter Demographics

The data shown below were collected from the profiles of 9 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 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 40 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 30%
Researcher 7 18%
Student > Master 6 15%
Student > Doctoral Student 3 8%
Student > Bachelor 3 8%
Other 5 13%
Unknown 4 10%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 23 57%
Agricultural and Biological Sciences 7 18%
Computer Science 2 5%
Chemistry 2 5%
Medicine and Dentistry 1 3%
Other 1 3%
Unknown 4 10%

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 31 July 2019.
All research outputs
of 21,243,519 outputs
Outputs from BMC Biology
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Outputs of similar age
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Outputs of similar age from BMC Biology
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Altmetric has tracked 21,243,519 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,819 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.0. This one is in the 40th percentile – i.e., 40% 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 288,676 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them