Emerging applications of single-cell diagnostics.
Topics in current chemistry, ISSN: 0340-1022, Vol: 336, Page: 99-116
2014
- 5Citations
- 10Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Citations5
- Citation Indexes5
- CrossRef5
- Captures10
- Readers10
- 10
Review Description
The performance of DNA sequencers (next generation sequencing) is rapidly enhanced these days, being used for genetic diagnostics. Although many phenomena could be elucidated with such massive genome data, it is still a big challenge to obtain comprehensive understanding of diseases and the relevant biology at the cellular level. In general terms, the data obtained to date are averages of ensembles of cells, but it is not certain whether the same features are the same inside an individual cell. Accordingly, important information may be masked by the averaging process. As the technologies for analyzing bio-molecular components in single cells are being developed, single cell analysis seems promising to address the current limitations due to averaging problems. Although the technologies for single cell analysis are still at the infant stage, the single cell approach has the potential to improve the accuracy of diagnosis based on knowledge of intra- and inter-cellular networks. In this review several technologies and applications (especially medical applications) of genome and transcriptome analysis or single cells are described.
Bibliographic Details
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