Supplemental Table 2: Bidirectional deep neural networks to integrate RNA and DNA data for predicting outcome of hepatocellular carcinoma patients.docx

Name: Supplemental Table 2: Bidirectional deep neural networks to integrate RNA and DNA data for predicting outcome of hepatocellular carcinoma patients.docx
Published: 2021-08-10T11:16:42+00:00
License: https://creativecommons.org/licenses/by-nc-nd/4.0/
Keywords: BiDNNs, multimodal autoencoders, multi-omics integration, survival, methylation, personalized cancer management, individualized patient profiling, unsupervised machine learning, Gene Expression (incl. Microarray and other genome-wide approaches), Genomics, Quantitative Genetics (incl. Disease and Trait Mapping Genetics), Cancer Genetics, Solid Tumours

dataset

posted on 2021-08-10, 11:16 authored by Guojun Huang, Wang Cheng, Fu Xi

Supplementary Table 2. Bidirectional deep neural networks to integrate RNA and DNA data for predicting outcome of hepatocellular carcinoma patients

Selection of the optimal cluster number

Supplemental Table 2: Bidirectional deep neural networks to integrate RNA and DNA data for predicting outcome of hepatocellular carcinoma patients.docx

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