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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Machine learning and systems genomics approaches for multi-omics data
|
|---|---|
| Published in |
Biomarker Research, January 2017
|
| DOI | 10.1186/s40364-017-0082-y |
| Pubmed ID | |
| Authors |
Eugene Lin, Hsien-Yuan Lane |
| Abstract |
In light of recent advances in biomedical computing, big data science, and precision medicine, there is a mammoth demand for establishing algorithms in machine learning and systems genomics (MLSG), together with multi-omics data, to weigh probable phenotype-genotype relationships. Software frameworks in MLSG are extensively employed to analyze hundreds of thousands of multi-omics data by high-throughput technologies. In this study, we reviewed the MLSG software frameworks and future directions with respect to multi-omics data analysis and integration. Our review was targeted at researching recent approaches and technical solutions for the MLSG software frameworks using multi-omics platforms. |
X Demographics
The data shown below were collected from the profiles of 17 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 | 7 | 41% |
| Colombia | 1 | 6% |
| Sweden | 1 | 6% |
| Chile | 1 | 6% |
| Germany | 1 | 6% |
| Iran, Islamic Republic of | 1 | 6% |
| United Kingdom | 1 | 6% |
| Unknown | 4 | 24% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 12 | 71% |
| Scientists | 2 | 12% |
| Practitioners (doctors, other healthcare professionals) | 2 | 12% |
| Science communicators (journalists, bloggers, editors) | 1 | 6% |
Mendeley readers
The data shown below were compiled from readership statistics for 378 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | <1% |
| Unknown | 377 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 77 | 20% |
| Student > Ph. D. Student | 71 | 19% |
| Student > Master | 47 | 12% |
| Student > Bachelor | 30 | 8% |
| Student > Doctoral Student | 22 | 6% |
| Other | 58 | 15% |
| Unknown | 73 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 84 | 22% |
| Agricultural and Biological Sciences | 55 | 15% |
| Computer Science | 53 | 14% |
| Medicine and Dentistry | 23 | 6% |
| Engineering | 20 | 5% |
| Other | 60 | 16% |
| Unknown | 83 | 22% |
Attention Score in Context
This research output has an Altmetric Attention Score of 23. 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 11 June 2023.
All research outputs
#1,578,032
of 24,410,879 outputs
Outputs from Biomarker Research
#10
of 360 outputs
Outputs of similar age
#33,668
of 425,487 outputs
Outputs of similar age from Biomarker Research
#1
of 7 outputs
Altmetric has tracked 24,410,879 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 360 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done particularly well, scoring higher than 97% 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 425,487 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 92% of its contemporaries.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them