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Large-scale gene network analysis reveals the significance of extracellular matrix pathway and homeobox genes in acute myeloid leukemia: an introduction to the Pigengene package and its applications

Overview of attention for article published in BMC Medical Genomics, March 2017
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  • Above-average Attention Score compared to outputs of the same age (64th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

facebook
1 Facebook page
wikipedia
4 Wikipedia pages

Citations

dimensions_citation
32 Dimensions

Readers on

mendeley
47 Mendeley
citeulike
1 CiteULike
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Title
Large-scale gene network analysis reveals the significance of extracellular matrix pathway and homeobox genes in acute myeloid leukemia: an introduction to the Pigengene package and its applications
Published in
BMC Medical Genomics, March 2017
DOI 10.1186/s12920-017-0253-6
Pubmed ID
Authors

Amir Foroushani, Rupesh Agrahari, Roderick Docking, Linda Chang, Gerben Duns, Monika Hudoba, Aly Karsan, Habil Zare

Abstract

The distinct types of hematological malignancies have different biological mechanisms and prognoses. For instance, myelodysplastic syndrome (MDS) is generally indolent and low risk; however, it may transform into acute myeloid leukemia (AML), which is much more aggressive. We develop a novel network analysis approach that uses expression of eigengenes to delineate the biological differences between these two diseases. We find that specific genes in the extracellular matrix pathway are underexpressed in AML. We validate this finding in three ways: (a) We train our model on a microarray dataset of 364 cases and test it on an RNA Seq dataset of 74 cases. Our model showed 95% sensitivity and 86% specificity in the training dataset and showed 98% sensitivity and 91% specificity in the test dataset. This confirms that the identified biological signatures are independent from the expression profiling technology and independent from the training dataset. (b) Immunocytochemistry confirms that MMP9, an exemplar protein in the extracellular matrix, is underexpressed in AML. (c) MMP9 is hypermethylated in the majority of AML cases (n=194, Welch's t-test p-value <10(-138)), which complies with its low expression in AML. Our novel network analysis approach is generalizable and useful in studying other complex diseases (e.g., breast cancer prognosis). We implement our methodology in the Pigengene software package, which is publicly available through Bioconductor. Eigengenes define informative biological signatures that are robust with respect to expression profiling technology. These signatures provide valuable information about the underlying biology of diseases, and they are useful in predicting diagnosis and prognosis.

Mendeley readers

The data shown below were compiled from readership statistics for 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 47 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 26%
Researcher 10 21%
Student > Postgraduate 4 9%
Student > Doctoral Student 3 6%
Student > Master 3 6%
Other 7 15%
Unknown 8 17%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 15 32%
Agricultural and Biological Sciences 8 17%
Medicine and Dentistry 4 9%
Computer Science 2 4%
Business, Management and Accounting 1 2%
Other 6 13%
Unknown 11 23%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 December 2019.
All research outputs
#3,877,355
of 13,457,774 outputs
Outputs from BMC Medical Genomics
#211
of 681 outputs
Outputs of similar age
#92,511
of 262,456 outputs
Outputs of similar age from BMC Medical Genomics
#7
of 12 outputs
Altmetric has tracked 13,457,774 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 681 research outputs from this source. They receive a mean Attention Score of 4.8. This one has gotten more attention than average, scoring higher than 68% 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 262,456 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 64% of its contemporaries.
We're also able to compare this research output to 12 others from the same source and published within six weeks on either side of this one. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.