Prior Knowledge Driven Joint NMF Algorithm for ceRNA Co-Module Identification
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Summary
The joint matrix factorization method integrating prior knowledge is developed to map the three types of RNA data of lung cancer to the common coordinate system and construct the ceRNA network corresponding to thecommon module, showing that more than 90% of the modules are closely related to cancer, including lung cancer.
- Type
- article
- Published
- 2018-10-19
- Cited by
- 17
- References
- 51
- Access
- Open access
- OpenAlex
- https://openalex.org/W2898335785
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:53425225
Keywords
Competing endogenous RNA, microRNA, Computational biology, Biology, Construct (python library)
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Cited by
- Competing endogenous network analysis identifies lncRNA Meg3 activates inflammatory damage in UVB induced murine skin lesion by sponging miR-93-5p/epiregulin axis
- LMSM: A modular approach for identifying lncRNA related miRNA sponge modules in breast cancer
- The Study of Sarcoma Microenvironment Heterogeneity Associated With Prognosis Based on an Immunogenomic Landscape Analysis
- miRSM: an R package to infer and analyse miRNA sponge modules in heterogeneous data
- Integration of Imaging Genomics Data for the Study of Alzheimer's Disease Using Joint-Connectivity-Based Sparse Nonnegative Matrix Factorization
- The LMCD1-AS1/miR-526b-3p/OSBPL5 axis promotes cell proliferation, migration and invasion in non-small cell lung cancer
- A Novel Constrained Non-negative Matrix Factorization Method for Group Functional Magnetic Resonance Imaging Data Analysis of Adult Attention-Deficit/Hyperactivity Disorder
- Comprehensive ceRNA network for MACF1 regulates osteoblast proliferation
- Integration of RNA molecules data with prior-knowledge driven Joint Deep Semi-Negative Matrix Factorization for heart failure study
- Application of orthogonal sparse joint non-negative matrix factorization based on connectivity in Alzheimer's disease research.
- Sparse Independence Component Analysis for Competitive Endogenous RNA Co-Module Identification in Liver Hepatocellular Carcinoma
- Integrating multi-omics data of childhood asthma using a deep association model
- A review on separation and application of plant-derived exosome-like nanoparticles.
- Deep self-reconstruction driven joint nonnegative matrix factorization model for identifying multiple genomic imaging associations in complex diseases
- Aging-Associated CASC15/hsa-miR-30c-5p/ SERPINE1 Axis Affects the Occurrence and Development of Gastric Cancer
- An Improved Deep Semi-supervised JNMF Method for Biomarker Extraction of Alzheimer’s Disease
- Scene: Inferring subtype-specific ceRNA modules in breast cancer
- Additional file 1 of The LMCD1-AS1/miR-526b-3p/OSBPL5 axis promotes cell proliferation, migration and invasion in non-small cell lung cancer
- LMSM: a modular approach for identifying lncRNA related miRNA sponge modules in breast cancer
- Integration of Imaging Genomics Data for the Study of Alzheimer's Disease Using Joint-Connectivity-Based Sparse Nonnegative Matrix Factorization
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