Professor Bradley Broom
- B.Sc.(First class honours in Computer Science, University of Queensland, 1983),
- Ph.D.(Computer Science, University of Queensland, 1988).
- Computer Science Research. My research has addressed numerous topics in computer science, including syntax-directed editors and related programming support systems, operating systems for distributed memory multi-computers, security for network information systems, and parallelizing compilers for high-performance computing systems.
- Welsh, J., Broom, B.M., Kiong, D. (1991). A design rationale for a language-based editor. Software—Practice and Experience, 21, 923-948.
- Ashley, P., Broom, B.M., Vandenwauver, M. (1999). Implementation of a secure version of NFS including RBAC. Australian Computer Journal, 31(2), 54-64.
- Broom, B.M., Fowler, R.J., Kennedy, K. (2002). KelpIO: A telescope-ready domain-specific I/O library for irregular block-structured applications. Future Generation Computer Systems, 18(4), 449-460.
- Kennedy, K., Broom, B.M., Chauhan, A., Fowler, R.J., Garvin, J., Koelbel, C., McCosh, C., Mellor-Crummey, J.M. (2005). Telescoping languages: a system for automatic generation of domain languages. Proceedings of the IEEE, 93(2), 387-408.
- Statistics, Biostatistics, and Bioinformatics Research. For nearly 20 years, I have contributed to the development of new tools and methodologies in the fields of statistics, biostatistics, and bioinformatics.
- Wood, A., Do, K.A., Broom, B.M. (1996). Sequential linearization of empirical likelihood constraints with application to U-statistics. Journal of Computational and Graphical Statistics, 5, 365-385.
- Do, K.-A., Broom, B.M., Wang, X. (2001). Importance bootstrap resampling for proportional hazards regression. Communications in statistics—Theory and Methods, 30(10), 2173-2188.
- Broom, B.M., Sulman, E.P., Do, K.A., Edgerton, M.E., Aldape, K.D. (2010). Bagged gene shaving for the robust clustering of high-throughput data. International Journal of Bioinformatics Research and Applications, 6(4), 326-43. PMCID: PMC3879957.
- Wang, W., Baladandayuthapani, V., Morris, J.S., Broom, B.M., Manyam, G., Do, K.A. (2013). Integrative Bayesian Analysis of High-dimensional Multi-platform Genomics Data. Bioinformatics, 29(2), 149-59. PMCID: PMC3546799.
- Collaborative Clinical and Biological Research. For 15 years, I have undertaken collaborative research with clinical and biological investigators. This research has primarily involved the analysis of data from microarrays and other high-throughput platforms in the context of cancer research. It includes participation in numerous TCGA analysis working groups, and well as research collaborations with other researchers in the prostate SPORE.
- Do, K-A., Broom, B.M., Kuhnert, P., Duffy, D.L., Todorov, A.A., Treloar, S.A., Martin, N.G. (2000). Genetic analysis of the age at menopause by using estimating equations and Bayesian random effects models. Statistics in Medicine, 19(9), 1217-1235.
- Cancer Genome Atlas Research Network. (2014). Comprehensive molecular characterization of urothelial bladder carcinoma. Nature, 507(7492), 315-22. PMCID: PMC3962515.
- Li, L., Chang, W., Yang, G., Ren, C., Park, S., Karantanos, T., Karanika, S., Wang, J., Yin, J., Shah, P.K., Takahiro, H., Dobashi, M., Zhang, W., Efstathiou, E., Maity, S.N., Aparicio, A.M., Li, Ning, Tapia E.M., Troncoso, P., Broom, B.M., Xiao, L.,Lee, H.S., Lee, J.S., Corn, P.G., Navone, N., Thompson, T.C. (2014). Targeting poly (ADP-ribose) polymerase and the c-Myb-regulated DNA damage response pathway in castration-resistant prostate cancer. Sci Signal, 7(326). PMCID: PMC4135429.
- Li, L, Karanika, S, Yang, G, Yang, Wang J, Park, S, Broom BM, Manyam, GC, Wu, W, Luo, Y, Basourakos, S, Song, JH, Gallick, GE, Karantanos, T, Korentzelos, D, Azad, AK, Kim, J, Corn, PG, Aparicio, AM, Logothesis CJ, Troncoso, P, Heffernan, T, Toniatti, C, Lee, HS, Lee, JS, Zuo, X, Chang, W, Yin, J, Timothy C. Thompson. Androgen receptor inhibitor-induced “BRCAness” and PARP inhibition are synthetically lethal for castration-resistant prostate cancer. Sci Signal, 10(480). PMCID: PMC5855082.
Professor Broom’s research interests include the analysis of high-throughput bioinformatics data, scientific visualization, machine learning, and reproducible analysis.
- FjORD, an enterprise information system for managing a large assortment of reproducible data analyses.
- GeneClust, an implementation of the “Gene Shaving” method for finding gene clusters.
- Next-Generation Clustered Heat Maps, large-scale interactive clustered heat maps suitable for the interactive exploration of large bioinformatics (and other) data sets.
- DyCE, a dynamic computational environment.
- MetaBatch, an Adaptation of the MBatch environment for detecting, evaluating, and ameliorating batch effects in Metabolomic data.