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Software . 2019
License: https://www.gnu.org/licenses/gpl-3.0-standalone.html
Data sources: Datacite
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Software . 2019
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Benchmark of computational methods for predicting microRNA-disease associations

integration_instructionsResearch softwarekeyboard_double_arrow_right Software 31 Aug 2019Publisher:Zenodo
Authors: Huang.Zhou; Liu.Leibo; Gao.Yuanxu; Shi.Jiangcheng; Cui.Qinghua; Li.Jianwei; Zhou.Yuan;

doi: 10.5281/zenodo.3383372 , 10.5281/zenodo.3383387 , 10.5281/zenodo.3383371

Benchmark of computational methods for predicting microRNA-disease associations

Abstract

Based on more than 8,000 novel miRNA-disease associations from the latest HMDD database, we performed systematic comparison among currently readily available prediction methods. The related source codes for implementing the benchmarking test were made available here. Source codes implemented on Python 2.7: PRC.py----------calculate AUPRC of predictors and plot PRC charts ROC.py----------calculate AUROC and plot ROC charts Max_min data.py----------iterative integration of predictors using their Max_min normalized results Sigmoid data.py----------iterative integration of predictors using their Sigmoid normalized results Z_score data.py----------iterative integration of predictors using their Z_score normalized results Original data.py----------iterative integration of predictors using their original results

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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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