The Boolean implication networks outperformed Bayesian networks, Pearson’s correlation networks, and other Boolean networks in constructing genome-scale co-expression networks evaluated with comprehensive biological pathways and Gene Ontology in MSigDB.

References:

Guo NL, Wan YW. Pathway-based identification of a smoking associated 6-gene signature predictive of lung cancer risk and survival. Artificial Intelligence in Medicine 2012 Jun;55(2):97-105.

Ye Q, Singh S, Qian PR, Guo NL. Immune-Omics Networks of CD27, PD1, and PDL1 in Non-Small Cell Lung Cancer. Cancers. 2021;13(17). Epub 2021/09/11. doi: 10.3390/cancers13174296. PubMed PMID: 34503105.

Features

  • Boolean implication networks
  • DNA copy number variation
  • Gene expression

Project Samples

CD27 networks

Project Activity

See All Activity >

Follow GENET-CNV

GENET-CNV Web Site

Other Useful Business Software
Build Agents and Models on One Platform Icon
Build Agents and Models on One Platform

Everything you need to build production-ready agents and models. Access 200+ Google and third-party AI models and tools.

Gemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
Try It Free
Rate This Project
Login To Rate This Project

User Reviews

Be the first to post a review of GENET-CNV!

Additional Project Details

Registered

2021-10-02
Report inappropriate content