Cargando…
Conserved Disease Modules Extracted From Multilayer Heterogeneous Disease and Gene Networks for Understanding Disease Mechanisms and Predicting Disease Treatments
Disease relationship studies for understanding the pathogenesis of complex diseases, diagnosis, prognosis, and drug development are important. Traditional approaches consider one type of disease data or aggregating multiple types of disease data into a single network, which results in important temp...
Autores principales: | Yu, Liang, Yao, Shunyu, Gao, Lin, Zha, Yunhong |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6346701/ https://www.ncbi.nlm.nih.gov/pubmed/30713550 http://dx.doi.org/10.3389/fgene.2018.00745 |
Ejemplares similares
-
Biased Random Walk With Restart on Multilayer Heterogeneous Networks for MiRNA–Disease Association Prediction
por: Qu, Jia, et al.
Publicado: (2021) -
Adapting Community Detection Algorithms for Disease Module Identification in Heterogeneous Biological Networks
por: Tripathi, Beethika, et al.
Publicado: (2019) -
Predicting LncRNA–Disease Association by a Random Walk With Restart on Multiplex and Heterogeneous Networks
por: Yao, Yuhua, et al.
Publicado: (2021) -
Application of Multilayer Network Models in Bioinformatics
por: Lv, Yuanyuan, et al.
Publicado: (2021) -
Decoding the heterogeneity of Alzheimer’s disease diagnosis and progression using multilayer networks
por: Avelar-Pereira, Bárbara, et al.
Publicado: (2022)