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Grouping of hypertension network. Features are sorted by their centrality in the cluster. (CSV)
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创建时间：
2021-02-12
相关数据集
Additional file 5 of Prediction of new associations between ncRNAs and diseases exploiting multi-type hierarchical clustering
Additional file 5 Comparative analysis of the ranking produced by lP-HCLUS and its competitors with respect to the new validated relationships in hMDD v3.2.
Figshare2020-02-25 更新70
Secondary vs. essential hypertension among 2704 patients with 3922 saccular intracranial aneurysms (sIAs) admitted to Kuopio University Hospital from the Eastern Finnish catchment population in 1995–2014.
Secondary vs. essential hypertension among 2704 patients with 3922 saccular intracranial aneurysms (sIAs) admitted to Kuopio University Hospital from the Eastern Finnish catchment population in 1995–2
NIAID Data Ecosystem30
Protein length versus number of taxonomy hits, by cluster.
Red: cluster A, dark blue: cluster B, light blue: cluster C, yellow: cluster D, magenta: cluster E, green: cluster F, brown: cluster G, grey: unclustered cloud.
Figshare2016-02-24 更新30
SH1043373.10FU
UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases
DataCite Commons2024-09-04 更新40
Deep learning enables accurate clustering with batch effect removal in single-cell RNA-seq analysis
The data was used to evaluate the performance of single cell RNA-Seq clustering methods. Overall design: The data was generated from human peripheral blood mononuclear clear cells by Ficoll Separation
NIAID Data Ecosystem30
