Associate Professor Brett Lidbury

Senior Fellow
Building 62 Mills Road Australian National University
 +61 2 6125 7875

Profile

Qualifications

B.Sc, B.Sc (Hons) (Newcastle) PhD (ANU) FFSc (RCPA).

Biography

I completed undergraduate and honours degrees at the University of Newcastle, followed by a Ph.D. at the ANU (JCSMR). Post-doctoral experience was gained in molecular virology and mucosal vaccine development, followed by a lecturing position (molecular biology, genetics, medical science) at the University of Canberra.

Further research on virus-host interaction and pathogenesis was conducted while attached to the Department of Microbiology and Immunology at the University of North Carolina-Chapel Hill in the United States, supported by a NIH-R01 grant.

In addition to the above, I have experience in diagnostic pathology and a period as a pre-clinical evaluator (toxicology) with the Therapeutic Goods Administration.

Interests in virology and pathogenesis have moved in silico, with the application of machine-learning/pattern-recognition techniques to support the study of human susceptibility or resistance to disease post viral infection (e.g. HBV). Techniques include recursive partitioning (trees) and support vector machines (SVMs), as both classification and regression applications to biomedical data. This research theme has diversified into other aspects of quality in diagnostic pathology, supported by the Quality Use of Pathology Programme (QUPP - Commonwealth Department of Health), and in collaboration with the Royal College of Pathologists (QAP) and NSW Health Pathology.

Chronic Fatigue Syndrome/Myalgic Encephalomyelitis (CFS/ME) studies are ongoing with research participants recruited and assessed by CFS Discovery in Melbourne, and in collaboration with the Hudson Research Institute, Paranta Biosciences, the Bio21 Institute (Melbourne) and JCSMR. The CFS/ME projects are funded by the Mason Foundation and ME Research UK.

Research

Research interests

  • Infection and Immunity (In silico)
  • Chronic disease (e.g. CFS/ME)
  • Diagnostic pathology

Animal alternatives (biomedical models)

Publications

  1. Richardson, A., B. M. Signor, B. A. Lidbury and T. Badrick (2016). Clinical chemistry in higher dimensions: Machine-learning and enhanced prediction from routine clinical chemistry data. Clin Biochem. http://dx.doi.org/10.1016/j.clinbiochem.2016.07.013
  2. Shang, G., B. J. Biggerstaff, A. M. Richardson, M. E. Gahan and B. A. Lidbury (2016). A simulation model to estimate the risk of transfusion-transmitted arboviral infection. Transfus Apher Sci. (In press)
  3. Taylor, A., J. V. Melton, L. J. Herrero, B. Thaa, L. Karo-Astover, P. W. Gage, M. A. Nelson, K. C. Sheng, B. A. Lidbury, G. D. Ewart, G. M. McInerney, A. Merits and S. Mahalingam (2016). Effects of an In-Frame Deletion of the 6k Gene Locus from the Genome of Ross River Virus.  J Virol 90:4150-4159.
  4. Lara J. Herrero, A. T., Pierre Roques, Brett A. Lidbury and Suresh Mahalingam. (2016). Animal Models of Alphavirus-induced Inflammatory Disease. Alphaviruses. L. Herrero, B. Herring. S. Mahalingam. Poole, UK, Caister Academic Press.
  5. Badrick, T., A. M. Richardson and B. A. Lidbury (2016). Response to article: serum total bilirubin concentrations are inversely associated with total white blood cell counts in an adult population. Ann Clin Biochem 53:412-413.
  6. Langley, G., C. P. Austin, A. K. Balapure, L. S. Birnbaum, J. R. Bucher, J. Fentem, S. C. Fitzpatrick, J. R. Fowle, 3rd, R. J. Kavlock, H. Kitano, B. A. Lidbury, A. R. Muotri, S. Q. Peng, D. Sakharov, T. Seidle, T. Trez, A. Tonevitsky, A. van de Stolpe, M. Whelan and C. Willett (2015). Lessons from Toxicology: Developing a 21st-Century Paradigm for Medical Research. Environ Health Perspect 123:A268-272.
  7. Badrick, T., A. M. Richardson, A. Arnott and B. A. Lidbury (2015). The early detection of anaemia and aetiology prediction through the modelling of red cell distribution width (RDW) in cross-sectional community patient data. Diagnosis 2:171-179.
  8. Lidbury, B. A., A. M. Richardson and T. Badrick (2015). Assessment of machine-learning techniques on large pathology data sets to address assay redundancy in routine liver function test profiles. Diagnosis 2:41-51.
  9. Lidbury, B. A. and S. Mahalingam (2014). Dengue virus and host antibody: a dangerous balancing act. Lancet Infect Dis 14:783-784.
  10. Chen, W., S. S. Foo, N. E. Rulli, A. Taylor, K. C. Sheng, L. J. Herrero, B. L. Herring, B. A. Lidbury, R. W. Li, N. C. Walsh, N. A. Sims, P. N. Smith and S. Mahalingam (2014). Arthritogenic alphaviral infection perturbs osteoblast function and triggers pathologic bone loss. Proc Natl Acad Sci U S A 111:6040-6045.

Updated:  26 May 2017/Responsible Officer:  Director/Page Contact:  Executive Support Officer