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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Discovering Altered Regulation and Signaling Through Network-based Integration of Transcriptomic, Epigenomic, and Proteomic Tumor Data
|
|---|---|
| Chapter number | 2 |
| Book title |
Cancer Systems Biology
|
| Published in |
Methods in molecular biology, January 2018
|
| DOI | 10.1007/978-1-4939-7493-1_2 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-7492-4, 978-1-4939-7493-1
|
| Authors |
Amanda J. Kedaigle, Ernest Fraenkel |
| Abstract |
With the extraordinary rise in available biological data, biologists and clinicians need unbiased tools for data integration in order to reach accurate, succinct conclusions. Network biology provides one such method for high-throughput data integration, but comes with its own set of algorithmic problems and needed expertise. We provide a step-by-step guide for using Omics Integrator, a software package designed for the integration of transcriptomic, epigenomic, and proteomic data. Omics Integrator can be found at http://fraenkel.mit.edu/omicsintegrator . |
X Demographics
The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 67% |
| India | 1 | 17% |
| Unknown | 1 | 17% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 6 | 100% |
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 % |
|---|---|---|
| Student > Ph. D. Student | 5 | 38% |
| Student > Bachelor | 3 | 23% |
| Researcher | 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 | 7 | 54% |
| Agricultural and Biological Sciences | 3 | 23% |
| Physics and Astronomy | 1 | 8% |
| Medicine and Dentistry | 1 | 8% |
| Unknown | 1 | 8% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 06 November 2018.
All research outputs
#13,342,820
of 23,016,919 outputs
Outputs from Methods in molecular biology
#3,493
of 13,165 outputs
Outputs of similar age
#213,855
of 442,354 outputs
Outputs of similar age from Methods in molecular biology
#327
of 1,498 outputs
Altmetric has tracked 23,016,919 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,165 research outputs from this source. They receive a mean Attention Score of 3.4. This one has gotten more attention than average, scoring higher than 72% 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 442,354 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 50% of its contemporaries.
We're also able to compare this research output to 1,498 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.