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Transcriptomic Studies of Malaria: a Paradigm for Investigation of Systemic Host-Pathogen Interactions

Overview of attention for article published in Microbiology & Molecular Biology Reviews, April 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (79th percentile)

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Title
Transcriptomic Studies of Malaria: a Paradigm for Investigation of Systemic Host-Pathogen Interactions
Published in
Microbiology & Molecular Biology Reviews, April 2018
DOI 10.1128/mmbr.00071-17
Pubmed ID
Authors

Hyun Jae Lee, Athina Georgiadou, Thomas D. Otto, Michael Levin, Lachlan J. Coin, David J. Conway, Aubrey J. Cunnington

Abstract

Transcriptomics, the analysis of genome-wide RNA expression, is a common approach to investigate host and pathogen processes in infectious diseases. Technical and bioinformatic advances have permitted increasingly thorough analyses of the association of RNA expression with fundamental biology, immunity, pathogenesis, diagnosis, and prognosis. Transcriptomic approaches can now be used to realize a previously unattainable goal, the simultaneous study of RNA expression in host and pathogen, in order to better understand their interactions. This exciting prospect is not without challenges, especially as focus moves from interactions in vitro under tightly controlled conditions to tissue- and systems-level interactions in animal models and natural and experimental infections in humans. Here we review the contribution of transcriptomic studies to the understanding of malaria, a parasitic disease which has exerted a major influence on human evolution and continues to cause a huge global burden of disease. We consider malaria a paradigm for the transcriptomic assessment of systemic host-pathogen interactions in humans, because much of the direct host-pathogen interaction occurs within the blood, a readily sampled compartment of the body. We illustrate lessons learned from transcriptomic studies of malaria and how these lessons may guide studies of host-pathogen interactions in other infectious diseases. We propose that the potential of transcriptomic studies to improve the understanding of malaria as a disease remains partly untapped because of limitations in study design rather than as a consequence of technological constraints. Further advances will require the integration of transcriptomic data with analytical approaches from other scientific disciplines, including epidemiology and mathematical modeling.

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X Demographics

The data shown below were collected from the profiles of 14 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 187 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 187 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 34 18%
Student > Master 34 18%
Researcher 32 17%
Student > Bachelor 14 7%
Student > Postgraduate 12 6%
Other 19 10%
Unknown 42 22%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 46 25%
Agricultural and Biological Sciences 35 19%
Immunology and Microbiology 24 13%
Medicine and Dentistry 10 5%
Computer Science 7 4%
Other 19 10%
Unknown 46 25%
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 29 September 2019.
All research outputs
#3,657,161
of 25,604,262 outputs
Outputs from Microbiology & Molecular Biology Reviews
#413
of 1,396 outputs
Outputs of similar age
#70,035
of 340,312 outputs
Outputs of similar age from Microbiology & Molecular Biology Reviews
#4
of 5 outputs
Altmetric has tracked 25,604,262 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,396 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.7. This one has gotten more attention than average, scoring higher than 70% 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 340,312 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 79% of its contemporaries.
We're also able to compare this research output to 5 others from the same source and published within six weeks on either side of this one.