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Cancerouspdomains: comprehensive analysis of cancer type-specific recurrent somatic mutations in proteins and domains

Overview of attention for article published in BMC Bioinformatics, August 2017
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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 (75th percentile)
  • High Attention Score compared to outputs of the same age and source (85th percentile)

Mentioned by

twitter
11 tweeters

Citations

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4 Dimensions

Readers on

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13 Mendeley
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Title
Cancerouspdomains: comprehensive analysis of cancer type-specific recurrent somatic mutations in proteins and domains
Published in
BMC Bioinformatics, August 2017
DOI 10.1186/s12859-017-1779-5
Pubmed ID
Authors

Seirana Hashemi, Abbas Nowzari Dalini, Adrin Jalali, Ali Mohammad Banaei-Moghaddam, Zahra Razaghi-Moghadam

Abstract

Discriminating driver mutations from the ones that play no role in cancer is a severe bottleneck in elucidating molecular mechanisms underlying cancer development. Since protein domains are representatives of functional regions within proteins, mutations on them may disturb the protein functionality. Therefore, studying mutations at domain level may point researchers to more accurate assessment of the functional impact of the mutations. This article presents a comprehensive study to map mutations from 29 cancer types to both sequence- and structure-based domains. Statistical analysis was performed to identify candidate domains in which mutations occur with high statistical significance. For each cancer type, the corresponding type-specific domains were distinguished among all candidate domains. Subsequently, cancer type-specific domains facilitated the identification of specific proteins for each cancer type. Besides, performing interactome analysis on specific proteins of each cancer type showed high levels of interconnectivity among them, which implies their functional relationship. To evaluate the role of mitochondrial genes, stem cell-specific genes and DNA repair genes in cancer development, their mutation frequency was determined via further analysis. This study has provided researchers with a publicly available data repository for studying both CATH and Pfam domain regions on protein-coding genes. Moreover, the associations between different groups of genes/domains and various cancer types have been clarified. The work is available at http://www.cancerouspdomains.ir .

Twitter Demographics

The data shown below were collected from the profiles of 11 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 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 13 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 31%
Student > Ph. D. Student 4 31%
Student > Bachelor 2 15%
Student > Master 1 8%
Other 1 8%
Other 0 0%
Unknown 1 8%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 5 38%
Agricultural and Biological Sciences 2 15%
Pharmacology, Toxicology and Pharmaceutical Science 1 8%
Medicine and Dentistry 1 8%
Neuroscience 1 8%
Other 1 8%
Unknown 2 15%

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 14 September 2017.
All research outputs
#3,649,404
of 19,255,221 outputs
Outputs from BMC Bioinformatics
#1,482
of 6,568 outputs
Outputs of similar age
#56,355
of 234,352 outputs
Outputs of similar age from BMC Bioinformatics
#2
of 7 outputs
Altmetric has tracked 19,255,221 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,568 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one has done well, scoring higher than 77% 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 234,352 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 75% of its contemporaries.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 5 of them.