Detailed Information
Cited 0 time in 
Cited 0 time in 
Cited 0 time in
Metadata Downloads
Estimation of joint directed acyclic graphs with lasso family for gene networks
- Authors
- Han, Sung Won; Park, Sunghoon; Zhong, Hua; Ryu, Eun-Seok; Wang, Pei; Jung, Sehee; Lim, Jayeon; Yoon, Jeewhan; Kim, SungHwan
- Issue Date
- 2021
- Publisher
- TAYLOR & FRANCIS INC
- Keywords
- Bayesian network; Drug response network; Lasso estimation; Probabilistic graphical model; Structure equation model; Unknown natural ordering
- Citation
- COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, v.50, no.9, pp.2793 - 2807
- Indexed
- SCIE
SCOPUS
- Volume
- 50
- Number
- 9
- Start Page
- 2793
- End Page
- 2807
- ISSN
- 0361-0918
- Abstract
- Biological regulatory pathways provide important information for target gene cancer therapy. Frequently, estimating the gene networks of two distinct patient groups is a worthwhile investigation. This paper proposes an approach, called jDAG, to the estimation of directed joint networks. It can identify common directed edges with joint data sets and distinct edges. In a simulation study, we show that the proposed jDAG outperforms existing methods although it does require longer computational times. We also present and discuss the example study of a breast cancer data set with ER + and ER-.
- Files in This Item
- There are no files associated with this item.
- Appears in
Collections - ETC > 1. Journal Articles
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.