| Title |
Next-generation molecular diagnosis: single-cell sequencing from bench to bedside
|
|---|---|
| Published in |
Cellular and Molecular Life Sciences, October 2016
|
| DOI | 10.1007/s00018-016-2368-x |
| Pubmed ID | |
| Authors |
Wanjun Zhu, Xiao-Yan Zhang, Sadie L. Marjani, Jialing Zhang, Wengeng Zhang, Shixiu Wu, Xinghua Pan |
| Abstract |
Single-cell sequencing (SCS) is a fast-growing, exciting field in genomic medicine. It enables the high-resolution study of cellular heterogeneity, and reveals the molecular basis of complicated systems, which facilitates the identification of new biomarkers for diagnosis and for targeting therapies. It also directly promotes the next generation of genomic medicine because of its ultra-high resolution and sensitivity that allows for the non-invasive and early detection of abnormalities, such as aneuploidy, chromosomal translocation, and single-gene disorders. This review provides an overview of the current progress and prospects for the diagnostic applications of SCS, specifically in pre-implantation genetic diagnosis/screening, non-invasive prenatal diagnosis, and analysis of circulating tumor cells. These analyses will accelerate the early and precise control of germline- or somatic-mutation-based diseases, particularly single-gene disorders, chromosome abnormalities, and cancers. |
X Demographics
The data shown below were collected from the profiles of 4 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 Kingdom | 2 | 50% |
| Finland | 1 | 25% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 4 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 86 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Malaysia | 1 | 1% |
| Sweden | 1 | 1% |
| Germany | 1 | 1% |
| Unknown | 83 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 16 | 19% |
| Student > Ph. D. Student | 15 | 17% |
| Student > Master | 10 | 12% |
| Lecturer | 6 | 7% |
| Student > Bachelor | 6 | 7% |
| Other | 17 | 20% |
| Unknown | 16 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 19 | 22% |
| Agricultural and Biological Sciences | 19 | 22% |
| Medicine and Dentistry | 14 | 16% |
| Engineering | 5 | 6% |
| Neuroscience | 4 | 5% |
| Other | 4 | 5% |
| Unknown | 21 | 24% |
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 24 February 2017.
All research outputs
#13,974,740
of 23,794,258 outputs
Outputs from Cellular and Molecular Life Sciences
#2,701
of 4,151 outputs
Outputs of similar age
#170,246
of 321,883 outputs
Outputs of similar age from Cellular and Molecular Life Sciences
#36
of 51 outputs
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