An RNA-seq Based Machine Learning Approach Identifies Latent Tuberculosis Patients With an Active Tuberculosis Profile

A better understanding of the response against Tuberculosis (TB) infection is required to accurately identify the individuals with an active or a latent TB infection (LTBI) and also those LTBI patients at higher risk of developing active TB. In this work, we have used the information obtained from s...

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書誌詳細
出版年:Front Immunol
主要な著者: Estévez, Olivia, Anibarro, Luis, Garet, Elina, Pallares, Ángeles, Barcia, Laura, Calviño, Laura, Maueia, Cremildo, Mussá, Tufária, Fdez-Riverola, Florentino, Glez-Peña, Daniel, Reboiro-Jato, Miguel, López-Fernández, Hugo, Fonseca, Nuno A., Reljic, Rajko, González-Fernández, África
フォーマット: Artigo
言語:Inglês
出版事項: Frontiers Media S.A. 2020
主題:
Immunology
オンライン･アクセス:https://ncbi.nlm.nih.gov/pmc/articles/PMC7372107/
https://ncbi.nlm.nih.gov/pubmed/32760401
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fimmu.2020.01470
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