ArticleIEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology proceedings. IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology2012
Matrix Factorization for Transcriptional Regulatory Network Inference.
Article in IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology proceedings. IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Disentangling factors affecting bacterial transcriptional regulatory network inference.iScience · 2026Article
- Reconstructing Dynamic Gene Regulatory Networks Using f-Divergence from Time-Series scRNA-Seq Data.Current issues in molecular biology · 2025Article
- PMF-GRN: a variational inference approach to single-cell gene regulatory network inference using probabilistic matrix factorization.Genome biology · 2024Article
- Inferring cellular and molecular processes in single-cell data with non-negative matrix factorization using Python, R and GenePattern Notebook implementations of CoGAPS.Nature protocols · 2023Review
- A primer on correlation-based dimension reduction methods for multi-omics analysis.Journal of the Royal Society, Interface · 2023Review
- CoGAPS 3: Bayesian non-negative matrix factorization for single-cell analysis with asynchronous updates and sparse data structures.BMC bioinformatics · 2020Article
- Integration of single-cell multi-omics for gene regulatory network inference.Computational and structural biotechnology journal · 2020Review
- DeepMF: deciphering the latent patterns in omics profiles with a deep learning method.BMC bioinformatics · 2019Article
- Assessing reproducibility of matrix factorization methods in independent transcriptomes.Bioinformatics (Oxford, England) · 2019Article
- Decomposing Cell Identity for Transfer Learning across Cellular Measurements, Platforms, Tissues, and Species.Cell systems · 2019Article
- Enter the Matrix: Factorization Uncovers Knowledge from Omics.Trends in genetics : TIG · 2018Review
- Integrated time course omics analysis distinguishes immediate therapeutic response from acquired resistance.Genome medicine · 2018Article
- PatternMarkers & GWCoGAPS for novel data-driven biomarkers via whole transcriptome NMF.Bioinformatics (Oxford, England) · 2017Article
- Article
- The non-negative matrix factorization toolbox for biological data mining.Source code for biology and medicine · 2013Article
- Preferential activation of the hedgehog pathway by epigenetic modulations in HPV negative HNSCC identified with meta-pathway analysis.PloS one · 2013Article
Corrections and comments
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2 authors.
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Abstract
Inference of Transcriptional Regulatory Networks (TRNs) provides insight into the mechanisms driving biological systems, especially mammalian development and disease. Many techniques have been developed for TRN estimation from indirect biochemical measurements. Although successful when initially tested in model organisms, these regulatory models often fail when applied to data from multicellular organisms where multiple regulation and gene reuse increase dramatically. Non-negative matrix factorization techniques were initially introduced to find non-orthogonal patterns in data, making them ideal techniques for inference in cases of multiple regulation. We review these techniques and their application to TRN analysis.
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