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Mendeley readers
Attention Score in Context
| Title |
Data Mining and Pattern Recognition Models for Identifying Inherited Diseases: Challenges and Implications
|
|---|---|
| Published in |
Frontiers in Genetics, August 2016
|
| DOI | 10.3389/fgene.2016.00136 |
| Pubmed ID | |
| Authors |
Lahiru Iddamalgoda, Partha S. Das, Achala Aponso, Vijayaraghava S. Sundararajan, Prashanth Suravajhala, Jayaraman K. Valadi |
| Abstract |
Data mining and pattern recognition methods reveal interesting findings in genetic studies, especially on how the genetic makeup is associated with inherited diseases. Although researchers have proposed various data mining models for biomedical approaches, there remains a challenge in accurately prioritizing the single nucleotide polymorphisms (SNP) associated with the disease. In this commentary, we review the state-of-art data mining and pattern recognition models for identifying inherited diseases and deliberate the need of binary classification- and scoring-based prioritization methods in determining causal variants. While we discuss the pros and cons associated with these methods known, we argue that the gene prioritization methods and the protein interaction (PPI) methods in conjunction with the K nearest neighbors' could be used in accurately categorizing the genetic factors in disease causation. |
X Demographics
The data shown below were collected from the profiles of 10 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Sri Lanka | 2 | 20% |
| Israel | 2 | 20% |
| United States | 2 | 20% |
| India | 2 | 20% |
| Switzerland | 1 | 10% |
| Unknown | 1 | 10% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 7 | 70% |
| Scientists | 2 | 20% |
| Unknown | 1 | 10% |
Mendeley readers
The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 6% |
| Unknown | 34 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 12 | 33% |
| Student > Ph. D. Student | 3 | 8% |
| Student > Master | 3 | 8% |
| Student > Bachelor | 2 | 6% |
| Professor | 1 | 3% |
| Other | 3 | 8% |
| Unknown | 12 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 6 | 17% |
| Biochemistry, Genetics and Molecular Biology | 5 | 14% |
| Computer Science | 5 | 14% |
| Neuroscience | 2 | 6% |
| Nursing and Health Professions | 1 | 3% |
| Other | 2 | 6% |
| Unknown | 15 | 42% |
Attention Score in Context
This research output has an Altmetric Attention Score of 9. 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 26 November 2018.
All research outputs
#3,703,573
of 22,882,389 outputs
Outputs from Frontiers in Genetics
#1,125
of 11,919 outputs
Outputs of similar age
#67,023
of 357,745 outputs
Outputs of similar age from Frontiers in Genetics
#12
of 49 outputs
Altmetric has tracked 22,882,389 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,919 research outputs from this source. They receive a mean Attention Score of 3.7. This one has done particularly well, scoring higher than 90% 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 357,745 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 81% of its contemporaries.
We're also able to compare this research output to 49 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.