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The Status, Quality, and Expansion of the NIH Full-Length cDNA Project: The Mammalian Gene Collection (MGC)

Overview of attention for article published in Genome Research, October 2004
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (97th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

news
1 news outlet
twitter
2 X users
patent
254 patents
wikipedia
21725 Wikipedia pages

Readers on

mendeley
723 Mendeley
citeulike
4 CiteULike
connotea
1 Connotea
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Article details
Title
The Status, Quality, and Expansion of the NIH Full-Length cDNA Project: The Mammalian Gene Collection (MGC)
Published in
Genome Research, October 2004
DOI 10.1101/gr.2596504
Pubmed ID
Authors

Daniela S Gerhard, Lukas Wagner, Elise A Feingold, Carolyn M Shenmen, Lynette H Grouse, Greg Schuler, Steven L Klein, Susan Old, Rebekah Rasooly, Peter Good, Mark Guyer, Allison M Peck, Jeffery G Derge, David Lipman, Francis S Collins, Wonhee Jang, Steven Sherry, Mike Feolo, Leonie Misquitta, Eduardo Lee, Kirill Rotmistrovsky, Susan F Greenhut, Carl F Schaefer, Kenneth Buetow, Tom I Bonner, David Haussler, Jim Kent, Mark Kiekhaus, Terry Furey, Michael Brent, Christa Prange, Kirsten Schreiber, Nicole Shapiro, Narayan K Bhat, Ralph F Hopkins, Florence Hsie, Tom Driscoll, M Bento Soares, Tom L Casavant, Todd E Scheetz, Michael J Brown-stein, Ted B Usdin, Shiraki Toshiyuki, Piero Carninci, Yulan Piao, Dawood B Dudekula, Minoru S H Ko, Koichi Kawakami, Yutaka Suzuki, Sumio Sugano, C E Gruber, M R Smith, Blake Simmons, Troy Moore, Richard Waterman, Stephen L Johnson, Yijun Ruan, Chia Lin Wei, S Mathavan, Preethi H Gunaratne, Jiaqian Wu, Angela M Garcia, Stephen W Hulyk, Edwin Fuh, Ye Yuan, Anna Sneed, Carla Kowis, Anne Hodgson, Donna M Muzny, John McPherson, Richard A Gibbs, Jessica Fahey, Erin Helton, Mark Ketteman, Anuradha Madan, Stephanie Rodrigues, Amy Sanchez, Michelle Whiting, Anup Madari, Alice C Young, Keith D Wetherby, Steven J Granite, Peggy N Kwong, Charles P Brinkley, Russell L Pearson, Gerard G Bouffard, Robert W Blakesly, Eric D Green, Mark C Dickson, Alex C Rodriguez, Jane Grimwood, Jeremy Schmutz, Richard M Myers, Yaron S N Butterfield, Malachi Griffith, Obi L Griffith, Martin I Krzywinski, Nancy Liao, Ryan Morin, Diana Palmquist, Anca S Petrescu, Ursula Skalska, Duane E Smailus, Jeff M Stott, Angelique Schnerch, Jacqueline E Schein, Steven J M Jones, Robert A Holt, Agnes Baross, Marco A Marra, Sandra Clifton, Kathryn A Makowski, Stephanie Bosak, Joel Malek

Abstract

The National Institutes of Health's Mammalian Gene Collection (MGC) project was designed to generate and sequence a publicly accessible cDNA resource containing a complete open reading frame (ORF) for every human and mouse gene. The project initially used a random strategy to select clones from a large number of cDNA libraries from diverse tissues. Candidate clones were chosen based on 5'-EST sequences, and then fully sequenced to high accuracy and analyzed by algorithms developed for this project. Currently, more than 11,000 human and 10,000 mouse genes are represented in MGC by at least one clone with a full ORF. The random selection approach is now reaching a saturation point, and a transition to protocols targeted at the missing transcripts is now required to complete the mouse and human collections. Comparison of the sequence of the MGC clones to reference genome sequences reveals that most cDNA clones are of very high sequence quality, although it is likely that some cDNAs may carry missense variants as a consequence of experimental artifact, such as PCR, cloning, or reverse transcriptase errors. Recently, a rat cDNA component was added to the project, and ongoing frog (Xenopus) and zebrafish (Danio) cDNA projects were expanded to take advantage of the high-throughput MGC pipeline.

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X Demographics

X Demographics

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

Geographical breakdown

Geographical breakdown
Country Count As %
United Kingdom 9 1%
United States 6 <1%
Germany 3 <1%
Korea, Republic of 2 <1%
Spain 2 <1%
Denmark 2 <1%
Canada 2 <1%
Singapore 1 <1%
Portugal 1 <1%
Other 5 <1%
Unknown 690 95%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Bachelor 142 20%
Student > Ph. D. Student 141 20%
Researcher 99 14%
Student > Master 86 12%
Other 26 4%
Other 98 14%
Unknown 131 18%
Readers by discipline
Readers by discipline Count As %
Agricultural and Biological Sciences 250 35%
Biochemistry, Genetics and Molecular Biology 166 23%
Medicine and Dentistry 72 10%
Chemistry 16 2%
Pharmacology, Toxicology and Pharmaceutical Science 12 2%
Other 60 8%
Unknown 147 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 32. 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 September 2026.
All research outputs
#1,357,529
of 27,448,172 outputs
Outputs from Genome Research
#512
of 4,602 outputs
Outputs of similar age
#1,720
of 82,910 outputs
Outputs of similar age from Genome Research
#2
of 56 outputs
Altmetric has tracked 27,448,172 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,602 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 17.2. This one has done well, scoring higher than 88% 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 82,910 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 97% 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 particularly well, scoring higher than 96% of its contemporaries.