moBRCA-net: a breast cancer subtype classification framework based on multi-omics attention neural networks - BMC Bioinformatics

  • 📰 BioMedCentral
  • ⏱ Reading Time:
  • 22 sec. here
  • 2 min. at publisher
  • 📊 Quality Score:
  • News: 12%
  • Publisher: 71%

Ai Ai Headlines News

Ai Ai Latest News,Ai Ai Headlines

An article published in BMCBioInformatics presents moBRCA-net: an interpretable deep learning-based breast cancer subtype classification framework that uses multi-omics datasets.

] were obtained, where each set consists of genes either up or down-regulated in each breast cancer subtype. For PAM50 genes, during the multi-omics data integration step, most of the genes were filtered out, and only 18 genes were left as the input for the classifier. As a result, 53 genes of the top 200 genes were the functional genes known for the breast cancer subtype .

The major contribution of our study resides within the multi-omics data integration strategy. To maintain the biological relationship between the multi omics features while integration, feature selection module was constructed to identify the informative breast cancer signature genes and the relation between the identified genes and other two omics features were built based on the promoter and the target relationship.

 

Thank you for your comment. Your comment will be published after being reviewed.
Please try again later.
We have summarized this news so that you can read it quickly. If you are interested in the news, you can read the full text here. Read more:

 /  🏆 22. in Aİ

Ai Ai Latest News, Ai Ai Headlines