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ZENODO
Dataset . 2020
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2020
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2020
License: CC BY
Data sources: ZENODO
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LDhat coalescent likelihood lookup table for 320 sequences with theta = 0.01

Authors: J. Steen Hoyer;

LDhat coalescent likelihood lookup table for 320 sequences with theta = 0.01

Abstract

The LDhat `complete` tool uses the method of Fearnhead and Donnelly (2001) to calculate coalescent likelihoods (via importance sampling) for all possible two-locus haplotype configurations for a given number of sequences for a grid of recombination rate (rho) values. See the LDhat documentation. We considered the case of 320 sequences, for which there are 708400 configurations. Generating this table was computationally expensive (approximately 60,000 CPU hours), hence the interest in sharing it for reuse. The included sbatch job script illustrates how the computations were done (with GNU Parallel). The script could be adapted to compute a similar table on Linux clusters that use Slurm for cluster management/job scheduling.

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citations
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.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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