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Motif-based analysis of large nucleotide data sets using MEME-ChIP

Overview of attention for article published in Nature Protocols, May 2014
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Title
Motif-based analysis of large nucleotide data sets using MEME-ChIP
Published in
Nature Protocols, May 2014
DOI 10.1038/nprot.2014.083
Pubmed ID
Authors

Wenxiu Ma, William S Noble, Timothy L Bailey

Abstract

MEME-ChIP is a web-based tool for analyzing motifs in large DNA or RNA data sets. It can analyze peak regions identified by ChIP-seq, cross-linking sites identified by CLIP-seq and related assays, as well as sets of genomic regions selected using other criteria. MEME-ChIP performs de novo motif discovery, motif enrichment analysis, motif location analysis and motif clustering, providing a comprehensive picture of the DNA or RNA motifs that are enriched in the input sequences. MEME-ChIP performs two complementary types of de novo motif discovery: weight matrix-based discovery for high accuracy; and word-based discovery for high sensitivity. Motif enrichment analysis using DNA or RNA motifs from human, mouse, worm, fly and other model organisms provides even greater sensitivity. MEME-ChIP's interactive HTML output groups and aligns significant motifs to ease interpretation. This protocol takes less than 3 h, and it provides motif discovery approaches that are distinct and complementary to other online methods.

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X Demographics

The data shown below were collected from the profiles of 5 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 382 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 6 2%
Canada 2 <1%
Spain 2 <1%
Sweden 1 <1%
Brazil 1 <1%
Italy 1 <1%
Mexico 1 <1%
Denmark 1 <1%
Korea, Republic of 1 <1%
Other 5 1%
Unknown 361 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 121 32%
Researcher 70 18%
Student > Master 48 13%
Student > Bachelor 31 8%
Student > Doctoral Student 17 4%
Other 54 14%
Unknown 41 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 144 38%
Biochemistry, Genetics and Molecular Biology 122 32%
Computer Science 15 4%
Medicine and Dentistry 10 3%
Immunology and Microbiology 9 2%
Other 31 8%
Unknown 51 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 30 November 2015.
All research outputs
#13,409,212
of 22,756,196 outputs
Outputs from Nature Protocols
#2,350
of 2,733 outputs
Outputs of similar age
#110,475
of 226,264 outputs
Outputs of similar age from Nature Protocols
#39
of 47 outputs
Altmetric has tracked 22,756,196 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,733 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.6. This one is in the 12th percentile – i.e., 12% 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 226,264 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 47 others from the same source and published within six weeks on either side of this one. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.