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Statistical and Machine Learning Approaches to Predict Gene Regulatory Networks From Transcriptome Datasets
Statistical and machine learning (ML)-based methods have recently advanced in construction of gene regulatory network (GRNs) based on high-throughput biological datasets. GRNs underlie almost all cellular phenomena; hence, comprehensive GRN maps are essential tools to elucidate gene function, thereb...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Frontiers Media S.A.
2018
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6281826/ https://www.ncbi.nlm.nih.gov/pubmed/30555503 http://dx.doi.org/10.3389/fpls.2018.01770 |