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ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2022
License: CC BY
Data sources: ZENODO
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Transcriptomic analysis of CTC at different timepoints

Authors: Diamantopoulou, Zoi; Castro-Giner, Francesc; Aceto, Nicola;

Transcriptomic analysis of CTC at different timepoints

Abstract

This work is supported by the European Research Council (#101001652), the Future and Emerging Technologies programme of the European Commission (grant 801159-B2B), the Swiss National Science Foundation (#PP00P3_190077), the Swiss Cancer League (#KLS-4834-08-2019), the Basel Cancer League (#KLbB-4763-02-2019), the two Cantons of Basel through the ETH Zürich (#PMB-01-16), the University of Basel and the ETH Zürich. Z. Diamantopoulou is a H2020 Marie Skłodowska-Curie Actions (#101028567) Fellow.

This repository contains processed transcriptomics data, large data sets and additional files related to the Diamantopoulou et al. (2022).

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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