Developmental gene regulatory network connections predicted by machine learning from gene expression data alone

Gene regulatory network (GRN) inference can now take advantage of powerful machine learning algorithms to complement traditional experimental methods in building gene networks. However, the dynamical nature of embryonic development–representing the time-dependent interactions between thousands of tr...

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Detalles Bibliográficos
Autores principales: Zhang, Jingyi, Ibrahim, Farhan, Najmulski, Emily, Katholos, George, Altarawy, Doaa, Heath, Lenwood S., Tulin, Sarah L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8714117/
https://www.ncbi.nlm.nih.gov/pubmed/34962963
http://dx.doi.org/10.1371/journal.pone.0261926

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8714117/
https://www.ncbi.nlm.nih.gov/pubmed/34962963
http://dx.doi.org/10.1371/journal.pone.0261926

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