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GCNG: graph convolutional networks for inferring gene interaction from spatial transcriptomics data
Most methods for inferring gene-gene interactions from expression data focus on intracellular interactions. The availability of high-throughput spatial expression data opens the door to methods that can infer such interactions both within and between cells. To achieve this, we developed Graph Convol...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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BioMed Central
2020
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7726911/ https://www.ncbi.nlm.nih.gov/pubmed/33303016 http://dx.doi.org/10.1186/s13059-020-02214-w |