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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Informatics for Nutritional Genetics and Genomics
|
|---|---|
| Chapter number | 7 |
| Book title |
Translational Informatics in Smart Healthcare
|
| Published in |
Advances in experimental medicine and biology, January 2017
|
| DOI | 10.1007/978-981-10-5717-5_7 |
| Pubmed ID | |
| Book ISBNs |
978-9-81-105716-8, 978-9-81-105717-5
|
| Authors |
Yuan Gao, Jiajia Chen |
| Abstract |
While traditional nutrition science is focusing on nourishing population, modern nutrition is aiming at benefiting individual people. The goal of modern nutritional research is to promote health, prevent diseases, and improve performance. With the development of modern technologies like bioinformatics, metabolomics, and molecular genetics, this goal is becoming more attainable. In this chapter, we will discuss the new concepts and technologies especially in informatics and molecular genetics and genomics, and how they have been implemented to change the nutrition science and lead to the emergence of new branches like nutrigenomics, nutrigenetics, and nutritional metabolomics. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 14 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 4 | 29% |
| Student > Bachelor | 2 | 14% |
| Student > Postgraduate | 2 | 14% |
| Student > Master | 2 | 14% |
| Professor | 1 | 7% |
| Other | 1 | 7% |
| Unknown | 2 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 2 | 14% |
| Agricultural and Biological Sciences | 2 | 14% |
| Veterinary Science and Veterinary Medicine | 1 | 7% |
| Nursing and Health Professions | 1 | 7% |
| Computer Science | 1 | 7% |
| Other | 5 | 36% |
| Unknown | 2 | 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 17 September 2017.
All research outputs
#15,479,632
of 23,002,898 outputs
Outputs from Advances in experimental medicine and biology
#2,515
of 4,961 outputs
Outputs of similar age
#257,307
of 421,223 outputs
Outputs of similar age from Advances in experimental medicine and biology
#235
of 490 outputs
Altmetric has tracked 23,002,898 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,961 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.1. This one is in the 37th percentile – i.e., 37% 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 421,223 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 490 others from the same source and published within six weeks on either side of this one. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.