| Title |
Discovery of biomarkers in rare diseases: innovative approaches by predictive and personalized medicine
|
|---|---|
| Published in |
EPMA Journal, December 2016
|
| DOI | 10.1186/s13167-016-0074-2 |
| Pubmed ID | |
| Authors |
Basri Gülbakan, Rıza Köksal Özgül, Ayşe Yüzbaşıoğlu, Matthias Kohl, Hans-Peter Deigner, Meral Özgüç |
| Abstract |
There are more than 8000 rare diseases (RDs) that affect >5 % of the world's population. Many of the RDs have no effective treatment and lack of knowledge creates delayed diagnosis making management difficult. The emerging concept of the personalized medicine allows for early screening, diagnosis, and individualized treatment of human diseases. In this context, the discovery of biomarkers in RDs will be of prime importance to enable timely prevention and effective treatment. Since 80 % of RDs are of genetic origin, identification of new genes and causative mutations become valuable biomarkers. Furthermore, dynamic markers such as expressed genes, metabolites, and proteins are also very important to follow prognosis and response the therapy. Recent advances in omics technologies and their use in combination can define pathophysiological pathways that can be drug targets. Biomarker discovery and their use in diagnosis in RDs is a major pillar in RD research. |
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 % |
|---|---|---|
| Netherlands | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Science communicators (journalists, bloggers, editors) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 121 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | <1% |
| Unknown | 120 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 15 | 12% |
| Student > Bachelor | 15 | 12% |
| Student > Master | 11 | 9% |
| Student > Ph. D. Student | 9 | 7% |
| Student > Doctoral Student | 5 | 4% |
| Other | 14 | 12% |
| Unknown | 52 | 43% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 25 | 21% |
| Medicine and Dentistry | 15 | 12% |
| Agricultural and Biological Sciences | 7 | 6% |
| Pharmacology, Toxicology and Pharmaceutical Science | 5 | 4% |
| Business, Management and Accounting | 3 | 2% |
| Other | 12 | 10% |
| Unknown | 54 | 45% |
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 09 December 2016.
All research outputs
#16,291,311
of 23,999,200 outputs
Outputs from EPMA Journal
#181
of 318 outputs
Outputs of similar age
#261,553
of 426,440 outputs
Outputs of similar age from EPMA Journal
#4
of 5 outputs
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