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An integrative analysis of small molecule transcriptional responses in the human malaria parasite Plasmodium falciparum

Overview of attention for article published in BMC Genomics, December 2015
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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 (77th percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

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Title
An integrative analysis of small molecule transcriptional responses in the human malaria parasite Plasmodium falciparum
Published in
BMC Genomics, December 2015
DOI 10.1186/s12864-015-2165-1
Pubmed ID
Authors

Geoffrey H. Siwo, Roger S. Smith, Asako Tan, Katrina A. Button-Simons, Lisa A. Checkley, Michael T. Ferdig

Abstract

Transcriptional responses to small molecules can provide insights into drug mode of action (MOA). The capacity of the human malaria parasite, Plasmodium falciparum, to respond specifically to transcriptional perturbations has been unclear based on past approaches. Here, we present the most extensive profiling to date of the parasite's transcriptional responsiveness to thirty-one chemically and functionally diverse small molecules. We exposed two laboratory strains of the human malaria parasite P. falciparum to brief treatments of thirty-one chemically and functionally diverse small molecules associated with biological effects across multiple pathways based on various levels of evidence. We investigated the impact of chemical composition and MOA on gene expression similarities that arise between perturbations by various compounds. To determine the target biological pathways for each small molecule, we developed a novel framework for encoding small molecule effects on a spectra of biological processes or GO functions that are enriched in the differentially expressed genes of a given small molecule perturbation. We find that small molecules associated with similar transcriptional responses contain similar chemical features, and/ or have a shared MOA. The approach also revealed complex relationships between drugs and biological pathways that are missed by most exisiting approaches. For example, the approach was able to partition small molecule responses into drug-specific effects versus non-specific effects. Our work provides a new framework for linking transcriptional responses to drug MOA in P. falciparum and can be generalized for the same purpose in other organisms.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Canada 1 3%
Unknown 37 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 24%
Researcher 6 16%
Student > Master 6 16%
Professor 2 5%
Lecturer 2 5%
Other 6 16%
Unknown 7 18%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 10 26%
Agricultural and Biological Sciences 10 26%
Chemistry 4 11%
Medicine and Dentistry 4 11%
Computer Science 2 5%
Other 1 3%
Unknown 7 18%
Attention Score in Context

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 03 October 2016.
All research outputs
#5,577,893
of 22,834,308 outputs
Outputs from BMC Genomics
#2,267
of 10,655 outputs
Outputs of similar age
#86,389
of 387,469 outputs
Outputs of similar age from BMC Genomics
#66
of 370 outputs
Altmetric has tracked 22,834,308 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 10,655 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done well, scoring higher than 78% 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 387,469 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 77% of its contemporaries.
We're also able to compare this research output to 370 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.