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Dataset . 2016
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Supporting Material: Improving The Identification Of Phenotypic Abnormalities And Sexual Dimorphism In Mice

Research datakeyboard_double_arrow_right Dataset 04 Nov 2016Publisher:Zenodo
Authors: Karp, Natasha A; Heller, Ruth; Yaacoby, Shay; White, Jacqueline K; Yoav, Benjamini;

doi: 10.5281/zenodo.164696

Supporting Material: Improving The Identification Of Phenotypic Abnormalities And Sexual Dimorphism In Mice

Abstract

Supporting material for the manuscript titled "Improving the Identification of Phenotypic Abnormalities and Sexual Dimorphism in Mice", accepted for publication in Genetics. This material enables a complete reproducible analysis of the results presented.

Related Organizations
Keywords

Sexual dimorphism, disease models, selective inference, discrete data, rare event data, High throughput phenotyping, multiple testing, mouse models

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visibility
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!
views
OpenAIRE UsageCountsViews provided by UsageCounts
0
Average
Average
Average
7