Statistical and machine learning methods for spatially resolved transcriptomics with histology

Recent developments in spatially resolved transcriptomics (SRT) technologies have enabled scientists to get an integrated understanding of cells in their morphological context. Applications of these technologies in diverse tissues and diseases have transformed our views of transcriptional complexity...

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Detalles Bibliográficos
Autores principales: Hu, Jian, Schroeder, Amelia, Coleman, Kyle, Chen, Chixiang, Auerbach, Benjamin J., Li, Mingyao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2021
Materias:
Review
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8273359/
https://www.ncbi.nlm.nih.gov/pubmed/34285782
http://dx.doi.org/10.1016/j.csbj.2021.06.052

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8273359/
https://www.ncbi.nlm.nih.gov/pubmed/34285782
http://dx.doi.org/10.1016/j.csbj.2021.06.052

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