ArticleInternational journal of biological sciences2018
Prior Knowledge Driven Joint NMF Algorithm for ceRNA Co-Module Identification.
Article in International journal of biological sciences, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 25 citations in OpenAlex.
- An Improved Deep Semi-supervised JNMF Method for Biomarker Extraction of Alzheimer's Disease.Journal of molecular neuroscience : MN · 2025Article
- Modeling ncRNA Synergistic Regulation in Cancer.Methods in molecular biology (Clifton, N.J.) · 2025Review
- Integrating multi-omics data of childhood asthma using a deep association model.Fundamental research · 2024Article
- Sparse Independence Component Analysis for Competitive Endogenous RNA Co-Module Identification in Liver Hepatocellular Carcinoma.IEEE journal of translational engineering in health and medicine · 2023Article
- Comprehensive ceRNA network for MACF1 regulates osteoblast proliferation.BMC genomics · 2022Article
- Integration of Imaging Genomics Data for the Study of Alzheimer's Disease Using Joint-Connectivity-Based Sparse Nonnegative Matrix Factorization.Journal of molecular neuroscience : MN · 2022Article
- The LMCD1-AS1/miR-526b-3p/OSBPL5 axis promotes cell proliferation, migration and invasion in non-small cell lung cancer.BMC pulmonary medicine · 2022Article
- A Novel Constrained Non-negative Matrix Factorization Method for Group Functional Magnetic Resonance Imaging Data Analysis of Adult Attention-Deficit/Hyperactivity Disorder.Frontiers in neuroscience · 2022Article
- Integration of RNA molecules data with prior-knowledge driven Joint Deep Semi-Negative Matrix Factorization for heart failure study.Frontiers in genetics · 2022Article
- miRSM: an R package to infer and analyse miRNA sponge modules in heterogeneous data.RNA biology · 2021Article
- LMSM: A modular approach for identifying lncRNA related miRNA sponge modules in breast cancer.PLoS computational biology · 2020Article
- The Study of Sarcoma Microenvironment Heterogeneity Associated With Prognosis Based on an Immunogenomic Landscape Analysis.Frontiers in bioengineering and biotechnology · 2020Article
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
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Abstract
MRNA and lncRNA serve as a type of endogenous RNA in cell, which can competitively bind to the same miRNA through miRNA response elements (MREs), thereby regulating their respective expression levels, playing an important role in post-transcriptional regulation, and regulating the progress of tumors. The proposed competing endogenous RNA (ceRNA) hypothesis provides novel clues for the occurrence and development of tumors, but the integrative analysis methods of diverse RNA data are significantly limited. In order to find out the relationship among miRNA, mRNA and lncRNA, the previous studies only used individual dataset as seeds to search two other related data in the database to construct ceRNA network, but it was difficult to identify the synchronized effects from multiple regulatory levels. Here, we developed the joint matrix factorization method integrating prior knowledge to map the three types of RNA data of lung cancer to the common coordinate system and construct the ceRNA network corresponding to the common module. The results show that more than 90% of the modules are closely related to cancer, including lung cancer. Furthermore, the resulting ceRNA network not only accurately excavates the known correlation of the three types of RNA molecular, but also further discovers the potential biological associations of them. Our work provides support and foundation for future biological validation how competitive relationships of multiple RNAs affects the development of tumors.
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