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Discovering transnosological molecular basis of human brain diseases using biclustering analysis of integrated gene expression data

Overview of attention for article published in BMC Medical Informatics and Decision Making, May 2015
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Title
Discovering transnosological molecular basis of human brain diseases using biclustering analysis of integrated gene expression data
Published in
BMC Medical Informatics and Decision Making, May 2015
DOI 10.1186/1472-6947-15-s1-s7
Pubmed ID
Authors

Kihoon Cha, Taeho Hwang, Kimin Oh, Gwan-Su Yi

Abstract

It has been reported that several brain diseases can be treated as transnosological manner implicating possible common molecular basis under those diseases. However, molecular level commonality among those brain diseases has been largely unexplored. Gene expression analyses of human brain have been used to find genes associated with brain diseases but most of those studies were restricted either to an individual disease or to a couple of diseases. In addition, identifying significant genes in such brain diseases mostly failed when it used typical methods depending on differentially expressed genes. In this study, we used a correlation-based biclustering approach to find coexpressed gene sets in five neurodegenerative diseases and three psychiatric disorders. By using biclustering analysis, we could efficiently and fairly identified various gene sets expressed specifically in both single and multiple brain diseases. We could find 4,307 gene sets correlatively expressed in multiple brain diseases and 3,409 gene sets exclusively specified in individual brain diseases. The function enrichment analysis of those gene sets showed many new possible functional bases as well as neurological processes that are common or specific for those eight diseases. This study introduces possible common molecular bases for several brain diseases, which open the opportunity to clarify the transnosological perspective assumed in brain diseases. It also showed the advantages of correlation-based biclustering analysis and accompanying function enrichment analysis for gene expression data in this type of investigation.

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

Geographical breakdown

Country Count As %
Unknown 16 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 31%
Student > Ph. D. Student 4 25%
Other 2 13%
Student > Master 2 13%
Student > Bachelor 1 6%
Other 2 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 3 19%
Psychology 3 19%
Medicine and Dentistry 3 19%
Computer Science 2 13%
Neuroscience 2 13%
Other 1 6%
Unknown 2 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 06 June 2015.
All research outputs
#14,225,412
of 22,805,349 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,101
of 1,988 outputs
Outputs of similar age
#138,484
of 266,611 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#25
of 43 outputs
Altmetric has tracked 22,805,349 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,988 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 38th percentile – i.e., 38% 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 266,611 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 43 others from the same source and published within six weeks on either side of this one. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.