↓ Skip to main content

Prediction of host - pathogen protein interactions between Mycobacterium tuberculosis and Homo sapiens using sequence motifs

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

About this Attention Score

  • Average Attention Score compared to outputs of the same age

Mentioned by

twitter
2 X users
facebook
1 Facebook page

Citations

dimensions_citation
50 Dimensions

Readers on

mendeley
92 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
Prediction of host - pathogen protein interactions between Mycobacterium tuberculosis and Homo sapiens using sequence motifs
Published in
BMC Bioinformatics, March 2015
DOI 10.1186/s12859-015-0535-y
Pubmed ID
Authors

Tong Huo, Wei Liu, Yu Guo, Cheng Yang, Jianping Lin, Zihe Rao

Abstract

Emergence of multiple drug resistant strains of M. tuberculosis (MDR-TB) threatens to derail global efforts aimed at reigning in the pathogen. Co-infections of M. tuberculosis with HIV are difficult to treat. To counter these new challenges, it is essential to study the interactions between M. tuberculosis and the host to learn how these bacteria cause disease. We report a systematic flow to predict the host pathogen interactions (HPIs) between M. tuberculosis and Homo sapiens based on sequence motifs. First, protein sequences were used as initial input for identifying the HPIs by 'interolog' method. HPIs were further filtered by prediction of domain-domain interactions (DDIs). Functional annotations of protein and publicly available experimental results were applied to filter the remaining HPIs. Using such a strategy, 118 pairs of HPIs were identified, which involve 43 proteins from M. tuberculosis and 48 proteins from Homo sapiens. A biological interaction network between M. tuberculosis and Homo sapiens was then constructed using the predicted inter- and intra-species interactions based on the 118 pairs of HPIs. Finally, a web accessible database named PATH (Protein interactions of M. tuberculosis and Human) was constructed to store these predicted interactions and proteins. This interaction network will facilitate the research on host-pathogen protein-protein interactions, and may throw light on how M. tuberculosis interacts with its host.

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 92 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 1%
Germany 1 1%
Ireland 1 1%
Unknown 89 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 20 22%
Researcher 15 16%
Student > Bachelor 13 14%
Student > Postgraduate 8 9%
Student > Master 8 9%
Other 14 15%
Unknown 14 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 26 28%
Biochemistry, Genetics and Molecular Biology 22 24%
Computer Science 7 8%
Medicine and Dentistry 4 4%
Immunology and Microbiology 3 3%
Other 13 14%
Unknown 17 18%
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 29 March 2015.
All research outputs
#15,327,280
of 22,796,179 outputs
Outputs from BMC Bioinformatics
#5,372
of 7,281 outputs
Outputs of similar age
#157,075
of 263,459 outputs
Outputs of similar age from BMC Bioinformatics
#105
of 139 outputs
Altmetric has tracked 22,796,179 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 7,281 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 18th percentile – i.e., 18% 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 263,459 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 139 others from the same source and published within six weeks on either side of this one. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.