Cancer subtype classification and modeling by pathway attention and propagation | Zendy

Sangseon Lee | Zendy; Sangsoo Lim | Zendy; Taeheon Lee | Zendy; Inyoung Sung | Zendy; ﻿Sun Kim | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Cancer subtype classification and modeling by pathway attention and propagation

Author(s) -

Sangseon Lee,

Sangsoo Lim,

Taeheon Lee,

Inyoung Sung,

Sun Kim

Publication year - 2020

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btaa203

Subject(s) - kegg , computational biology , biological pathway , mechanism (biology) , computer science , cancer , biological network , gene , source code , gene regulatory network , bioinformatics , biology , artificial intelligence , gene expression , genetics , transcriptome , philosophy , epistemology , operating system

Biological pathway is an important curated knowledge of biological processes. Thus, cancer subtype classification based on pathways will be very useful to understand differences in biological mechanisms among cancer subtypes. However, pathways include only a fraction of the entire gene set, only one-third of human genes in KEGG, and pathways are fragmented. For this reason, there are few computational methods to use pathways for cancer subtype classification.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research