Senior Research Officer
Dr Groza received his PhD from Digital Enterprise Research Institute, National University of Ireland, Galway in 2010. His thesis focused on representing, extracting and integrating scientific artefacts externalised via scientific publications.
In 2010 he joined The University of Queensland to work on the SKELETOME Project – a community-driven knowledge curation platform for bone dysplasias. As part of this project he developed novel methods to perform phenotype concept recognition, to decompose phenotypes into their elementary entity-quality forms, and to infer characteristic phenotypes using patient or domain data as background knowledge.
Tudor’s current research covers the entire phenotype analytics stack, from representation to acquisition (from publications or clinical reports) and from cross-species integration to decision making (including disorder prediction or patient matchmaking). Any prospective PhD students interested in undertaking research in these areas are welcome to get in touch and discuss collaboration opportunities.
In the NewsLeading genomic data projects to drive a new ‘world of knowledge’ - Oct 18, 2017
“The best tool of its kind in the world”: Patient Archive being used to advance diagnosis of rare diseases in WA - Apr 07, 2017
2016 Shine Translational Research Fellowship awarded - May 21, 2016
MyGene2 website reaches Open Science Prize final - May 12, 2016
Awards and Honours
2012 - ARC Discovery Early Career Researcher Award
2012 - UQ ResTeach Award
2011 - UQ New Staff Research Start-up Fund Award
2009 - Elsevier Grand Challenge, second place prize winner
2005 – MSc, Technical University of Cluj-Napoca – Romania
2004 – BSc, Technical University of Cluj-Napoca – Romania
Paul, R, Groza, T, Hunter, J, Zankl, A. Inferring characteristic phenotypes via class association rule mining in the bone dysplasia domain. Journal of Biomedical Informatics. 2014;48:73-83.
Paul, R, Groza, T, Hunter, J, Zankl, A. Semantic interestingness measures for discovering association rules in the skeletal dysplasia domain. Journal of Biomedical Semantics. 2014;5(1):8.
Collier N, Oellrich A, Groza T. Toward knowledge support for analysis and interpretation of complex traits. Genome Biology. 2013;14(9):214.
Groza, T, Hunter, J, Zankl, A. Decomposing phenotype descriptions for the Human Skeletal Phenome. Biomedical Informatics Insights. 2013;6:1-14.
Groza, T, Hunter, J, Zankl, A. Mining skeletal phenotype descriptions from scientific literature. PLoS One. 2013;8(2):e55656.
Groza, T, Hunter, J, Zankl, A. Supervised segmentation of phenotype descriptions for the human skeletal phenome using hybrid methods. BMC Bioinformatics. 2012;13:265.
Paul, R, Groza, T, Zankl, A, Hunter, J. Decision support methods for finding phenotype-disorder associations in the bone dysplasia domain. PLoS One. 2012;7(11):e50614.
Groza, T, Hunter, J, Zankl, A. The Bone Dysplasia Ontology: Integrating genotype and phenotype information in the skeletal dysplasia domain. BMC Bioinformatics. 2012;13(50)
Dr Tudor GrozaEmail: Click here to Email