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Miguel A. Juárez
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2020 – today
- 2020
- [j4]Miguel A. Juárez
, Marzio Pennisi, Giulia Russo
Generation of digital patients for the simulation of tuberculosis with UISS-TB. BMC Bioinform. 21-S(17): 449 (2020) - [j3]Giulia Russo
Moving forward through the in silico modeling of tuberculosis: a further step with UISS-TB. BMC Bioinform. 21-S(17): 458 (2020) - [j2]Marco Viceconti
Credibility of In Silico Trial Technologies - A Theoretical Framing. IEEE J. Biomed. Health Informatics 24(1): 4-13 (2020)
2010 – 2019
- 2019
- [c2]Marzio Pennisi, Miguel A. Juárez, Giulia Russo
Generation of digital patients for the simulation of tuberculosis with UISS-TB. BIBM 2019: 2163-2167 - [c1]Giulia Russo
Evaluation of the efficacy of RUTI and ID93/GLA-SE vaccines in tuberculosis treatment: in silico trial through UISS-TB simulator. BIBM 2019: 2197-2201 - [i2]Marco Viceconti, Miguel A. Juárez, Cristina Curreli, Marzio Pennisi, Giulia Russo, Francesco Pappalardo:
POSITION PAPER: Credibility of In Silico Trial Technologies: A Theoretical Framing. CoRR abs/1909.04660 (2019) - [i1]Marzio Pennisi, Miguel A. Juárez, Giulia Russo, Marco Viceconti, Francesco Pappalardo:
Generation of digital patients for the simulation of tuberculosis with UISS-TB. CoRR abs/1910.12293 (2019) - 2010
- [j1]Edward R. Morrissey
On reverse engineering of gene interaction networks using time course data with repeated measurements. Bioinform. 26(18): 2305-2312 (2010)
Coauthor Index
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