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High-resolution quantitative proteomics applied to the study of the specific protein signature in the sputum and saliva of active tuberculosis patients and their infected and uninfected contacts.
Mateos J, Estévez O, González-Fernández Á, Anibarro L, Pallarés Á, Reljic R, Gallardo JM, Medina I, Carrera M. Mateos J, et al. Among authors: pallares a. J Proteomics. 2019 Mar 20;195:41-52. doi: 10.1016/j.jprot.2019.01.010. Epub 2019 Jan 18. J Proteomics. 2019. PMID: 30660769 Clinical Trial.
An RNA-seq Based Machine Learning Approach Identifies Latent Tuberculosis Patients With an Active Tuberculosis Profile.
Estévez O, Anibarro L, Garet E, Pallares Á, Barcia L, Calviño L, Maueia C, Mussá T, Fdez-Riverola F, Glez-Peña D, Reboiro-Jato M, López-Fernández H, Fonseca NA, Reljic R, González-Fernández Á. Estévez O, et al. Among authors: pallares a. Front Immunol. 2020 Jul 14;11:1470. doi: 10.3389/fimmu.2020.01470. eCollection 2020. Front Immunol. 2020. PMID: 32760401 Free PMC article.
44 results