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Uncovering low-dimensional, miR-based signatures of acute myeloid and lymphoblastic leukemias with a machine-learning-driven network approach

Complex phenotypic differences among different acute leukemias cannot be fully captured by analyzing the expression levels of one single molecule, such as a miR, at a time, but requires systematic analysis of large sets of miRs. While a popular approach for analysis of such datasets is principal com...

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Dades bibliogràfiques
Publicat a:Converg Sci Phys Oncol
Autors principals: Candia, Julián, Cherukuri, Srujana, Guo, Yin, Doshi, Kshama A., Banavar, Jayanth R., Civin, Curt I., Losert, Wolfgang
Format: Artigo
Idioma:Inglês
Publicat: 2015
Matèries:
Accés en línia:https://ncbi.nlm.nih.gov/pmc/articles/PMC4888874/
https://ncbi.nlm.nih.gov/pubmed/27274862
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1088/2057-1739/1/2/025002
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