Enabling high-throughput single-animal gene-expression studies with molecular and micro-scale technologies
Lab on a Chip, ISSN: 1473-0189, Vol: 20, Issue: 24, Page: 4528-4538
2020
- 4Citations
- 12Captures
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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
- Citations4
- Citation Indexes4
- CrossRef4
- Captures12
- Readers12
- 12
Review Description
Gene expression and regulation play diverse and important roles across all living systems. By quantifying the expression, whether in a sample of single cells, a specific tissue, or in a whole animal, one can gain insights into the underlying biology. Many biological questions now require single-animal and tissue-specific resolution, such as why individuals, even within an isogenic population, have variations in development and aging across different tissues and organs. The popular techniques that quantify the transcriptome (e.g. RNA-sequencing) process populations of animals and cells together and thus, have limitations in both individual and spatial resolution. There are single-animal assays available (e.g. fluorescent reporters); however, they suffer other technical bottlenecks, such as a lack of robust sample-handling methods. Microfluidic technologies have demonstrated various improvements throughout the years, and it is likely they can enhance the impact of these single-animal gene-expression assays. In this perspective, we aim to highlight how the engineering/method-development field have unique opportunities to create new tools that can enable us to robustly answer the next set of important questions in biology that require high-density, high-quality gene expression data.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85098457896&origin=inward; http://dx.doi.org/10.1039/d0lc00881h; http://www.ncbi.nlm.nih.gov/pubmed/33237042; https://xlink.rsc.org/?DOI=D0LC00881H; https://dx.doi.org/10.1039/d0lc00881h; https://pubs.rsc.org/en/content/articlelanding/2020/lc/d0lc00881h
Royal Society of Chemistry (RSC)
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