Single cells make big data: New challenges and opportunities in transcriptomics is a research paper published in Current Opinion in Systems Biology (2017). On theSindex it has a DataRank of 0.833. It has been cited 257 times.
Recent technological advances have enabled unprecedented insight into transcriptomics at the level of single cells. Single cell transcriptomics enables the measurement of tran- scriptomic information of thousands of single cells in a single experiment. The volume and complexity of resulting data make it a paradigm of big data. Consequently, the field is presented with new scientific and, in particular, analytical challenges where currently no scalable solutions exist. At the same time, exciting opportunities arise from increased resolution of single- cell RNA sequencing data and improved statistical power of ever growing datasets. Big single cell RNA sequencing data promises valuable insights into cellular heterogeneity which may significantly improve our understanding of biology and human disease. This review focuses on single cell tran- scriptomics and highlights the inherent opportunities and challenges in the context of big data analytics.
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Base Score Contribution
0.833
From this paper's citation signal
Citation Network Contribution
0
Citation network not refreshed for this result
This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.
Learn more about DataRank methodology →DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 100% comes from its base citations and 0% from the citation network.
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.