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Representational Oligonucleotide Microarray Analysis: A High-Resolution Method to Detect Genome Copy Number Variation

Overview of attention for article published in Genome Research, January 2003
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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 (96th percentile)
  • High Attention Score compared to outputs of the same age and source (89th percentile)

Mentioned by

blogs
1 blog
patent
134 patents
wikipedia
4 Wikipedia pages

Citations

dimensions_citation
379 Dimensions

Readers on

mendeley
214 Mendeley
citeulike
7 CiteULike
connotea
2 Connotea
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Title
Representational Oligonucleotide Microarray Analysis: A High-Resolution Method to Detect Genome Copy Number Variation
Published in
Genome Research, January 2003
DOI 10.1101/gr.1349003
Pubmed ID
Authors

Robert Lucito, John Healy, Joan Alexander, Andrew Reiner, Diane Esposito, Maoyen Chi, Linda Rodgers, Amy Brady, Jonathan Sebat, Jennifer Troge, Joseph A West, Seth Rostan, Ken C Q Nguyen, Scott Powers, Kenneth Q Ye, Adam Olshen, Ennapadam Venkatraman, Larry Norton, Michael Wigler

Abstract

We have developed a methodology we call ROMA (representational oligonucleotide microarray analysis), for the detection of the genomic aberrations in cancer and normal humans. By arraying oligonucleotide probes designed from the human genome sequence, and hybridizing with "representations" from cancer and normal cells, we detect regions of the genome with altered "copy number." We achieve an average resolution of 30 kb throughout the genome, and resolutions as high as a probe every 15 kb are practical. We illustrate the characteristics of probes on the array and accuracy of measurements obtained using ROMA. Using this methodology, we identify variation between cancer and normal genomes, as well as between normal human genomes. In cancer genomes, we readily detect amplifications and large and small homozygous and hemizygous deletions. Between normal human genomes, we frequently detect large (100 kb to 1 Mb) deletions or duplications. Many of these changes encompass known genes. ROMA will assist in the discovery of genes and markers important in cancer, and the discovery of loci that may be important in inherited predispositions to disease.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 214 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 8 4%
United Kingdom 4 2%
Australia 2 <1%
Germany 2 <1%
Belgium 2 <1%
Portugal 1 <1%
Netherlands 1 <1%
Canada 1 <1%
Japan 1 <1%
Other 1 <1%
Unknown 191 89%

Demographic breakdown

Readers by professional status Count As %
Researcher 67 31%
Student > Ph. D. Student 39 18%
Student > Bachelor 22 10%
Student > Master 18 8%
Professor > Associate Professor 16 7%
Other 34 16%
Unknown 18 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 101 47%
Biochemistry, Genetics and Molecular Biology 35 16%
Medicine and Dentistry 26 12%
Engineering 9 4%
Computer Science 7 3%
Other 15 7%
Unknown 21 10%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 18. 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 02 April 2024.
All research outputs
#2,053,838
of 25,374,917 outputs
Outputs from Genome Research
#1,001
of 4,425 outputs
Outputs of similar age
#4,255
of 136,764 outputs
Outputs of similar age from Genome Research
#6
of 56 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,425 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 17.3. 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 136,764 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 96% of its contemporaries.
We're also able to compare this research output to 56 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.