A multi-component power-law penalty corrects distance bias in single-cell co-accessibility and deep-learning chromatin interaction predictions
Schlegel, Luca; gomez cano, fabio andres; marand, alexandre; Frank, Johannes;
A multi-component power-law penalty corrects distance bias in single-cell co-accessibility and deep-learning chromatin interaction predictions
This archive contains the source code, penalty parameters, and large-scale penalized co-accessibility datasets for Soybean, Rice, and Maize as described in the associated manuscript.
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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).
Citations provided by BIP!popularityPopularity provided by BIP!
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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