Prediction of developmental chemical toxicity based on gene networks of human embryonic stem cells

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Predictive toxicology using stem cells or their derived tissues has gained increasing importance in biomedical and pharmaceutical research. Here, we show that toxicity category prediction by support vector machines (SVMs), which uses qRT-PCR data from 20 categorized chemicals based on a human embryo...

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Detalles Bibliográficos
Autores principales: Yamane, Junko, Aburatani, Sachiyo, Imanishi, Satoshi, Akanuma, Hiromi, Nagano, Reiko, Kato, Tsuyoshi, Sone, Hideko, Ohsako, Seiichiroh, Fujibuchi, Wataru
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2016
Materias:
Computational Biology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4937330/
https://www.ncbi.nlm.nih.gov/pubmed/27207879
http://dx.doi.org/10.1093/nar/gkw450

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4937330/
https://www.ncbi.nlm.nih.gov/pubmed/27207879
http://dx.doi.org/10.1093/nar/gkw450

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