| Title |
Mutual enrichment in ranked lists and the statistical assessment of position weight matrix motifs
|
|---|---|
| Published in |
Algorithms for Molecular Biology, April 2014
|
| DOI | 10.1186/1748-7188-9-11 |
| Pubmed ID | |
| Authors |
Limor Leibovich, Zohar Yakhini |
| Abstract |
Statistics in ranked lists is useful in analysing molecular biology measurement data, such as differential expression, resulting in ranked lists of genes, or ChIP-Seq, which yields ranked lists of genomic sequences. State of the art methods study fixed motifs in ranked lists of sequences. More flexible models such as position weight matrix (PWM) motifs are more challenging in this context, partially because it is not clear how to avoid the use of arbitrary thresholds. |
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.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Venezuela, Bolivarian Republic of | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 5% |
| Unknown | 20 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 5 | 24% |
| Student > Ph. D. Student | 4 | 19% |
| Student > Master | 3 | 14% |
| Student > Bachelor | 2 | 10% |
| Professor > Associate Professor | 2 | 10% |
| Other | 2 | 10% |
| Unknown | 3 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 6 | 29% |
| Computer Science | 5 | 24% |
| Medicine and Dentistry | 3 | 14% |
| Biochemistry, Genetics and Molecular Biology | 2 | 10% |
| Engineering | 2 | 10% |
| Other | 0 | 0% |
| Unknown | 3 | 14% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 31 July 2014.
All research outputs
#15,301,167
of 22,756,196 outputs
Outputs from Algorithms for Molecular Biology
#148
of 264 outputs
Outputs of similar age
#132,914
of 226,073 outputs
Outputs of similar age from Algorithms for Molecular Biology
#8
of 10 outputs
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