Cargando…
Identification of More Feasible MicroRNA–mRNA Interactions within Multiple Cancers Using Principal Component Analysis Based Unsupervised Feature Extraction
MicroRNA(miRNA)–mRNA interactions are important for understanding many biological processes, including development, differentiation and disease progression, but their identification is highly context-dependent. When computationally derived from sequence information alone, the identification should b...
Autor principal: | Taguchi, Y-h. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4881522/ https://www.ncbi.nlm.nih.gov/pubmed/27171078 http://dx.doi.org/10.3390/ijms17050696 |
Ejemplares similares
-
Principal Component Analysis Based Feature Extraction Approach to Identify Circulating microRNA Biomarkers
por: Taguchi, Y-h., et al.
Publicado: (2013) -
Tensor Decomposition-Based Unsupervised Feature Extraction Can Identify the Universal Nature of Sequence-Nonspecific Off-Target Regulation of mRNA Mediated by MicroRNA Transfection
por: Taguchi, Y.-H.
Publicado: (2018) -
Principal component analysis based unsupervised feature extraction applied to budding yeast temporally periodic gene expression
por: Taguchi, Y-h
Publicado: (2016) -
Effects of Collagen–Glycosaminoglycan Mesh on Gene Expression as Determined by Using Principal Component Analysis-Based Unsupervised Feature Extraction
por: Taguchi, Y-h., et al.
Publicado: (2021) -
Principal Components Analysis Based Unsupervised Feature Extraction Applied to Gene Expression Analysis of Blood from Dengue Haemorrhagic Fever Patients
por: Taguchi, Y-h.
Publicado: (2017)