I am interested in Bayesian hierarchical modelling for panel and longitudinal data, in particular to address problems in biology, medicine and econometrics. Specifically,

I am working on models that integrate computer simulations with clinical trials in order to reduce their length and size.

I am working on models for the analysis of super-resolution microscopy images.
I am developing shrinkage priors for variable selection.
I have devised mixture models capable of accommodating skewness and non-Gaussian tail behaviour in econometrics.
I have been involved in developing models for systems biology, trying to understand gene regulatory networks.
I am also interested in objective Bayesian methods and their relationship with measures of information.

Kiagias et al. (2021) Bayesian augmented clinical trials in TB therapeutic vaccination, Frontiers in Medical Technology, 3. DOI: 10.3389/fmedt.2021.719380

Curreli, C et al. (2021) Verification of an agent-based disease model of human mycobacterium tuberculosis infection, International Journal for Numerical Methods in Biomedical Engineering, e3470.

Sharpe, JA and Juárez, MA (2021) Estimation of the Pareto and related distributions—a reference-intrinsic approach, Communications in Statistics ‐ Theory and Methods, DOI: 10.1080/03610926.2021.1916826.

Juárez MA, Pennisi M, Russo G, Kiagias D, Curreli C, Viceconti M and Pappalardo F (2020) Generation of digital patients for the simulation of tuberculosis with UISS‑TB BMC Bioinformatics 21 449.

Russo G, Sgroi G, Parasiliti Palumbo GA et al. (2020) Moving forward through the in silico modeling of tuberculosis: a further step with UISS-TB. BMC Bioinformatics 21 458.

Buck, CE and Juárez, MA, (2020) Modelización bayesiana de radiocarbono para principiatnes, Métodos cronométricos en arqueología, historia y paleontología (Barceló, JA and Morell, B eds), Chapter 13, 293–310.

Viceconti, M, Juárez, MA, Curreli, C,  Pennisi, M,  Russo, G and Pappalardo, F. (2020) Credibility of In Silico Trial Technologies–A Theoretical Framing,  IEEE Journal of Biomedical and Health Informatics, 24, 4–13. (DOI: 10.1109/JBHI.2019.2949888)

Alenazi, AA,  Cox, A,  Juárez, M,  Lin, W-Y,  Walters, K.(2019)  Bayesian variable selection using partially observed categorical prior information in fine-mapping association studies. Genet. Epidemiol. 43: 690– 703. (DOI 10.1002/gepi.22213)

G. Russo et al. (2019) Evaluation of the efficacy of RUTI and ID93/GLA-SE vaccines in tuberculosis treatment: in silico trial through UISS-TB simulator,  IEEE International Conference on Bioinformatics and Biomedicine (BIBM), San Diego, USA, pp. 2197–2201, (DOI: 10.1109/BIBM47256.2019.8983060)

Barnett, SFH et al (2017). A Novel Application of Non-Destructive Readout Technology to Localisation Microscopy.  Nature Scientific Reports 7 (DOI: 10.1038/srep42313)

Baker, D et al (2016).  Detecting genetic mosaicism in cultures of human pluripotent stem cells.  Stem Cell Reports 5, 998—1012 (DOI:10.1016/j.stemcr.2016.10.003)

Morrissey, E.R., Juárez, M.A., Denby, K.J. and Burroughs, N.J. (2011).  Inferring the time-invariant topology of a non-linear sparse gene regulatory network using fully Bayesian spline autoregression. Biostatistics 12, 682—694 (DOI:10.1093/biostatistics/kxr009)

Morrissey, E.R., Juárez, M.A., Denby, K.J. and Burroughs, N.J. (2010).  On reverse engineering of gene interaction networks using time course data with repeated measurements.   Bioinformatics, 26, 2305—2312 (DOI:10.1093/bioinformatics/btq421).

STREAM Consortium (2010). The dynamic architecture of the metabolic switch in Streptomyces coelicolor. BMC Genomics 2010, 11:10 (DOI:10.1186/1471-2164-11-10)

Juárez, M. A. and Steel, M. F. J. (2010).  Model-Based Clustering of Non-Gaussian Panel Data Based on Skew-t Distributions.   Journal of Business and Economic Statistics, 28, 52—66 (DOI: 10.1198/jbes.2009.07145).

Juárez, M. A. and Steel, M. F. J. (2010).  Non-Gaussian Dynamic Bayesian Modelling for Panel Data.  Journal of Applied Econometrics, 25, 1128—1154 (DOI: 10.1002/jae.1113).

Ferreira, JTAS; Juárez, MA and Steel, MFJ (2008).  Directional log-spline distributions.  Bayesian Analysis, 3, 267—315. (DOI:10.1214/08-BA311).

Bernardo, J. M. and Juárez, M. A. (2003).  Intrinsic estimation. Bayesian Statistics 7, Oxford: University Press, 465—476.

de Alba, E., Juárez, M. A. and Moreno, M.T. (1998). Bayesian Estimation of IBNR Reserves, Transactions of the International Congress of Actuaries Vol. 4, 255—273, Birmingham, England.

de Alba, E. and Juárez, M. A. (1995). Bayesian Forecasting: An Application to IBNR Claims Reserves, ASA Proceedings of the Section on Bayesian Statistical Science, 189—194.

Juárez, M. A. (2005a).  Objective Bayes estimation and hypothesis testing: the reference-intrinsic approach on non-regular models. CRiSM working paper 05-14.

Juárez, M. A. (2005b).  Objective Bayes inference on the normal correlation coefficient.  CRiSM working paper 05-15.