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KlinkeLab/CellNetwork_2020: v1.0.0

integration_instructionsResearch softwarekeyboard_double_arrow_right Software 10 Mar 2022Publisher:Zenodo
Authors: David Klinke; arcoolbaugh;

doi: 10.5281/zenodo.6345205 , 10.5281/zenodo.6345206

KlinkeLab/CellNetwork_2020: v1.0.0

Abstract

This initial release of the GitHub repository supplies the code developed in the study of D.J. Klinke, A. Fernandez, W. Deng, H. Latifizadeh, and A.C. Pirkey "Data-driven learning how oncogenic gene expression locally alters heterocellular networks". The corresponding pre-print can be found on bioRxiv ( doi: https://doi.org/10.1101/2020.05.04.077107). It can be used to reproduce the results of the study and investigate the methodology to be used for other datasets. Full Changelog: https://github.com/KlinkeLab/CellNetwork_2020/commits/v1.0.0

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selected citations
These citations are derived from selected sources.
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).
BIP!Citations provided by BIP!
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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