Ontology-aware classification of tissue and cell-type signals in gene expression profiles across platforms and technologies

Motivation: Leveraging gene expression data through large-scale integrative analyses for multicellular organisms is challenging because most samples are not fully annotated to their tissue/cell-type of origin. A computational method to classify samples using their entire gene expression profiles is...

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Detalles Bibliográficos
Autores principales: Lee, Young-suk, Krishnan, Arjun, Zhu, Qian, Troyanskaya, Olga G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2013
Materias:
Original Papers
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3834796/
https://www.ncbi.nlm.nih.gov/pubmed/24037214
http://dx.doi.org/10.1093/bioinformatics/btt529

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3834796/
https://www.ncbi.nlm.nih.gov/pubmed/24037214
http://dx.doi.org/10.1093/bioinformatics/btt529

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