ArticleOncotarget2017
ndmaSNF: cancer subtype discovery based on integrative framework assisted by network diffusion model.
Article in Oncotarget, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Network Approaches for Precision Oncology.Advances in experimental medicine and biology · 2022Article
- Ranking cancer drivers via betweenness-based outlier detection and random walks.BMC bioinformatics · 2021Article
- A new method for mining information of co-expression network based on multi-cancers integrated data.BMC medical genomics · 2019Article
- Semi-supervised prediction of protein interaction sites from unlabeled sample information.BMC bioinformatics · 2019Article
- Pathway analysis of genomic pathology tests for prognostic cancer subtyping.Journal of biomedical informatics · 2019Article
- The Emerging Potential for Network Analysis to Inform Precision Cancer Medicine.Journal of molecular biology · 2018Review
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3 authors.
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Abstract
Recently, with the rapid progress of high-throughput sequencing technology, diverse genomic data are easy to be obtained. To effectively exploit the value of those data, integrative methods are urgently needed. In this paper, based on SNF (Similarity Network Diffusion) [1], we proposed a new integrative method named ndmaSNF (network diffusion model assisted SNF), which can be used for cancer subtype discovery with the advantage of making use of somatic mutation data and other discrete data. Firstly, we incorporate network diffusion model on mutation data to make it smoothed and adaptive. Then, the mutation data along with other data types are utilized in the SNF framework by constructing patient-by-patient similarity networks for each data type. Finally, a fused patient network containing all the information from different input data types is obtained by using a nonlinear iterative method. The fused network can be used for cancer subtype discovery through the clustering algorithm. Experimental results on four cancer datasets showed that our ndmaSNF method can find subtypes with significant differences in the survival profile and other clinical features.
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