数据链接：
官方服务：
资源简介：
The data used for CODE-AE biclustering analysis
应用场景：
创建时间：
2021-09-29
相关数据集
Human PPI dataset ; Features dataset ; Autoencoder Model
Human Dataset
DataCite Commons2020-08-25 更新120
Autoencoder trained on transcriptomic signals
(A) Microarray normalised gene expression data used in reverse training to define the disease modules: MicroarrayDataForDiseaseGene.zip (B) 3 layer deep autoencoder trained on the 20K microarra
DataCite Commons2020-08-26 更新60
ARBic: an all-round biclustering algorithm for analyzing gene expression data
datasets of ARBic: an all-round biclustering algorithm for analyzing gene expression data
NIAID Data Ecosystem40
the code of autoencoder
Key features were extracted using an autoencoder-based approach from transcriptomic and copy number alteration (CNA) data of the TCGA-LIHC cohort. The associated analysis scripts and source code are p
Figshare2025-10-29 更新60
Code Repository from the paper: "An interpretable and adaptive autoencoder for efficient tissue deconvolution".
Code repository from the paper "An interpretable and adaptive autoencoder for efficient tissue deconvolution".Original Github repository here: https://github.com/ML4BM-Lab/Sweetwater.
DataCite Commons2025-07-21 更新50
