On reverse engineering of gene interaction networks using time course data with repeated measurements. - Edward R. Morrissey; Miguel A. Juárez; Katherine J. Denby; Nigel J. Burroughs (Bioinform., 2010)

Generation of digital patients for the simulation of tuberculosis with UISS-TB. - Marzio Pennisi; Miguel A. Juárez; Giulia Russo; Marco Viceconti; Francesco Pappalardo 001 (BIBM, 2019)

Evaluation of the efficacy of RUTI and ID93/GLA-SE vaccines in tuberculosis treatment: in silico trial through UISS-TB simulator. - Giulia Russo; Francesco Pappalardo 001; Miguel A. Juárez; Marzio Pennisi; Pere-Joan Cardona; Rhea Coler; Epifanio Fichera; Marco Viceconti (BIBM, 2019)

POSITION PAPER: Credibility of In Silico Trial Technologies: A Theoretical Framing. - Marco Viceconti; Miguel A. Juárez; Cristina Curreli; Marzio Pennisi; Giulia Russo; Francesco Pappalardo 001 (CoRR, 2019)

Generation of digital patients for the simulation of tuberculosis with UISS-TB. - Miguel A. Juárez; Marzio Pennisi; Giulia Russo; Dimitrios Kiagias; Cristina Curreli; Marco Viceconti; Francesco Pappalardo 001 (BMC Bioinform., 2020)

Moving forward through the in silico modeling of tuberculosis: a further step with UISS-TB. - Giulia Russo; Giuseppe Sgroi; Giuseppe Alessandro Parasiliti Palumbo; Marzio Pennisi; Miguel A. Juárez; Pere-Joan Cardona; Santo Motta; Kenneth B. Walker; Epifanio Fichera; Marco Viceconti; Francesco Pappalardo 001 (BMC Bioinform., 2020)

Credibility of In Silico Trial Technologies - A Theoretical Framing. - Marco Viceconti; Miguel A. Juárez; Cristina Curreli; Marzio Pennisi; Giulia Russo; Francesco Pappalardo 001 (IEEE J. Biomed. Health Informatics, 2020)