↓ Skip to main content

Pathprinting: An integrative approach to understand the functional basis of disease

Overview of attention for article published in Genome Medicine, July 2013
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (88th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
16 tweeters
f1000
1 research highlight platform

Citations

dimensions_citation
8 Dimensions

Readers on

mendeley
65 Mendeley
citeulike
5 CiteULike
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
Pathprinting: An integrative approach to understand the functional basis of disease
Published in
Genome Medicine, July 2013
DOI 10.1186/gm472
Pubmed ID
Authors

Gabriel M Altschuler, Oliver Hofmann, Irina Kalatskaya, Rebecca Payne, Shannan J Ho Sui, Uma Saxena, Andrei V Krivtsov, Scott A Armstrong, Tianxi Cai, Lincoln Stein, Winston A Hide, Altschuler GM, Hofmann O, Kalatskaya I, Payne R, Ho Sui SJ, Saxena U, Krivtsov AV, Armstrong SA, Cai T, Stein L, Hide WA

Abstract

New strategies to combat complex human disease require systems approaches to biology that integrate experiments from cell lines, primary tissues and model organisms. We have developed Pathprint, a functional approach that compares gene expression profiles in a set of pathways, networks and transcriptionally regulated targets. It can be applied universally to gene expression profiles across species. Integration of large-scale profiling methods and curation of the public repository overcomes platform, species and batch effects to yield a standard measure of functional distance between experiments. We show that pathprints combine mouse and human blood developmental lineage, and can be used to identify new prognostic indicators in acute myeloid leukemia. The code and resources are available at http://compbio.sph.harvard.edu/hidelab/pathprint.

Twitter Demographics

The data shown below were collected from the profiles of 16 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 65 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 3%
Belgium 1 2%
Sri Lanka 1 2%
Japan 1 2%
Italy 1 2%
Unknown 59 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 19 29%
Student > Ph. D. Student 17 26%
Student > Master 7 11%
Other 5 8%
Student > Bachelor 4 6%
Other 9 14%
Unknown 4 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 27 42%
Biochemistry, Genetics and Molecular Biology 15 23%
Computer Science 6 9%
Neuroscience 3 5%
Mathematics 2 3%
Other 6 9%
Unknown 6 9%

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 30 April 2017.
All research outputs
#1,680,371
of 15,466,446 outputs
Outputs from Genome Medicine
#425
of 1,055 outputs
Outputs of similar age
#18,774
of 159,734 outputs
Outputs of similar age from Genome Medicine
#6
of 11 outputs
Altmetric has tracked 15,466,446 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,055 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 23.6. This one has gotten more attention than average, scoring higher than 59% 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 159,734 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 88% of its contemporaries.
We're also able to compare this research output to 11 others from the same source and published within six weeks on either side of this one. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.