2019 update: This project has made some very good progress in 2019, with Jessica Chung providing the expertise from our team to enable development of a method to normalise cycle stage effects in endometrium expression data developed an interactive R Shiny application where the research group can explore microarray and RNA-seq data with their own […]
Assoc Prof Bernard Pope & Assoc Prof Daniel Park lead this group
|University of Melbourne||LEAD INSTITUTE|
Several grants support this group. See listing below.
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The Human Genomics Group is focused on enabling medical breakthroughs via new and cutting-edge bioinformatic approaches. We are leaders in developing novel approaches to solve large-scale data-analytics problems, as evidenced by our publications in field-leading journals, track record in attracting competitive research funding, and our strong collaborative links with other high-profile research partners in Australia and overseas. We actively engage in higher education and professional training in bioinformatics, and regularly supervise postgraduate research students.
Prospective Research Projects
An example of a very successful collaboration with this Group is the work being done on a range of colorectal cancer projects for the Buchanan Lab. In 2017 Dr Bernard Pope was awarded a Victorian Health and Medical Research Fellowship, funded by the Victorian Government, to further support his work on the prevention and treatment of colorectal cancer, arising from this collaboration. This four-year Fellowship, commenced in 2018, is focussed on the development of genomics-driven bioinformatics solutions to address two key areas where current clinical practice in the detection of colorectal cancer can be enhanced by considering the richer evidence provided by modern genomics technologies, offering a more personalised approach to diagnosis and risk assessment.
Please contact our team regarding collaborations and subscriptions via email@example.com.
Assoc Prof Daniel Park (Academic Lead, Melbourne Bioinformatics)
Assoc Prof Bernard Pope (Lead Bioinformatician for Cancer Genomics. Lead Bioinformatician for Clinical Genomics. Lecturer, MSc (Bioinformatics). Victorian Government Health and Medical Research Fellow, 2017-2021)
Dr Chol-hee Jung (Bioinformatician)
Dr Khalid Mahmood (Bioinformatician)
Dr Gayle Philip (Bioinformatician)
Ms Jessica Chung (Bioinformatician)
Ms Juny Kesumadewi (Software Developer)
Team members have been authors on the following publications:
Walsh, M., Bell, K.M., Chong, B., Creed, E., Brett, G.R., Pope, K., Thorne, N.P., Sadedin, S., Georgeson, P., Phelan, D.G., Day, T., Taylor, J.A., Sexton, A., Lockhart, P.J., Kiers, L., Fahey, M., Macciocca, I., Gaff, C.L., 2017. Diagnostic and cost utility of whole exome sequencing in peripheral neuropathy. Annals of Clinical and Translational Neurology, 2017 May; 4(5): 318–325. [DOI 10.1002/acn3.409]
Mahmood, K., Jung, C.H., Philip, G., Georgeson, P., Chung, J., Pope, B. and Park, D.J., 2017. Variant effect prediction tools assessed using independent, functional assay-based datasets: implications for discovery and diagnostics. Human Genomics, 11:10 [DOI 10.1186/s40246-017-0104-8]. Refer blog post.
Baglietto, L., Ponzi, E., Haycock, P., Hodge, A., Bianca Assumma, M., Jung, C.H., Chung, J., Fasanelli, F., Guida, F., Campanella, G. and Chadeau‐Hyam, M., 2017. DNA methylation changes measured in pre‐diagnostic peripheral blood samples are associated with smoking and lung cancer risk. International Journal of Cancer, 140(1), pp.50-61.
Quek, C., Bellingham, S.A., Jung, C.H., Scicluna, B., Shambrook, M.C., Sharples, R., Cheng, L. and Hill, A.F., 2016. Defining the purity of exosomes required for diagnostic profiling of small RNA suitable for biomarker discovery. RNA biology, (just-accepted), pp.00-00.
Jung, C.H., Kim, K.J., Kim, B.Y., Kim, C.H., Kang, S.K. and Mok, J.O., 2016. Relationship between vitamin D status and vascular complications in patients with type 2 diabetes mellitus. Nutrition Research, 36(2), pp.117-124.
MacInnis, R.J., …, Park, D.J., …, et al. Use of a novel nonparametric version of DEPTH to identify genomic regions associated with prostate cancer risk. Cancer Epidemiology, Biomarkers & Prevention doi:10.1158/1055-9965.EPI-16-0301 (2016).
Stark, Z., Tan, T. Y., Chong, B., Brett, G. R., Yap, P., Walsh, M., Yeung, A., Peters, H., Mordaunt, D., Cowie, S., Amor, D. J., Savarirayan, R., McGillivray, G., Downie, L., Ekert, P. G., Theda, C., James, P. A., Yaplito-Lee, J., Ryan, M. M., Leventer, R. J., Creed, E., Macciocca, I., Bell, K. M., Oshlack, A., Sadedin, S., Georgeson, P., Anderson, C., Thorne, N., Melbourne Genomics Health Alliance, Gaff, C. & White, S. M. A prospective evaluation of whole-exome sequencing as a first-tier molecular test in infants with suspected monogenic disorders. Genet. Med. 18, 1090–1096 (2016).
Dugue, P.A., …, Park, D.J., Chung, J., …, Jung, C.-H., …, et al. Genome-wide measures of DNA methylation in peripheral blood and the risk of urothelial cell carcinoma: a prospective nested case-control study. British Journal of Cancer doi:10.1038/bjc.2016.237 (2016).
Pope, B. J., Mahmood, K., Jung, C.-H., Georgeson, P. & Park, D. J. Single nucleotide-level mapping of DNA double-strand breaks in human HEK293T cells. Genomics Data doi:10.1016/j.gdata.2016.11.007 (2016).
Pope, B. J., Mahmood, K., Jung, C.-H. & Park, D. J. Fine resolution mapping of double-strand break sites for human ribosomal DNA units. Genom Data 10, 19–21 (2016).
Wong, N. C., Pope, B. J. (*), Candiloro, I. L., Korbie, D., Trau, M., Wong, S. Q., Mikeska, T., Zhang, X., Pitman, M., Eggers, S., Doyle, S. R. & Dobrovic, A. MethPat: a tool for the analysis and visualisation of complex methylation patterns obtained by massively parallel sequencing. BMC Bioinformatics 17, 98 (2016). (* Joint first author)
Dugué, P.-A., English, D. R., MacInnis, R. J., Jung, C.-H., Bassett, J. K., Fitzgerald, L. M., Wong, E. M., Joo, J. E., Hopper, J. L., Southey, M. C., Giles, G. G. & Milne, R. L. Reliability of DNA methylation measures from dried blood spots and mononuclear cells using the Human Methylation450k BeadArray. Sci. Rep. 6, 30317 (2016).
Hasmad, H. N., Lai, K. N., Wen, W. X., Park, D. J., Nguyen-Dumont, T., Kang, P. C. E., Thirthagiri, E., Ma’som, M., Lim, B. K., Southey, M., Woo, Y. L. & Teo, S.-H. Evaluation of germline BRCA1 and BRCA2 mutations in a multi-ethnic Asian cohort of ovarian cancer patients. Gynecol. Oncol. 141, 318–322 (2016).
Wong Doo, N., Makalic, E., Joo, J. E., Vajdic, C. M., Schmidt, D. F., Wong, E. M., Jung, C.-H., Severi, G., Park, D. J., Chung, J., Baglietto, L., Prince, H. M., Seymour, J. F., Tam, C., Hopper, J. L., English, D. R., Milne, R. L., Harrison, S. J., Southey, M. C. & Giles, G. G. Global measures of peripheral blood-derived DNA methylation as a risk factor in the development of mature B-cell neoplasms. Epigenomics 8, 55–66 (2016).
Park, D. J., Li, R., Lau, E., Georgeson, P., Nguyen-Dumont, T. & Pope, B. J. UNDR ROVER – a fast and accurate variant caller for targeted DNA sequencing. BMC Bioinformatics 17, 165 (2016).
Lawrence, S. L., Gorman, M. A., Feil, S. C., Mulhern, T. D., Kuiper, M. J., Ratner, A. J., Tweten, R. K., Morton, C. J. & Parker, M. W. Structural Basis for Receptor Recognition by the Human CD59-Responsive Cholesterol-Dependent Cytolysins. Structure 24, 1488–1498 (2016).
Wade, K. R., Hotze, E. M., Kuiper, M. J., Morton, C. J., Parker, M. W. & Tweten, R. K. An intermolecular electrostatic interaction controls the prepore-to-pore transition in a cholesterol-dependent cytolysin. Proc. Natl. Acad. Sci. U. S. A. 112, 2204–2209 (2015).
Kuiper, M. J., Morton, C. J., Abraham, S. E. & Gray-Weale, A. The biological function of an insect antifreeze protein simulated by molecular dynamics. Elife 4, (2015).
Wong, N. C., Pope, B. J. (*), Candiloro, I., Korbie, D., Trau, M., Wong, S. Q., Mikeska, T., van Denderen, B. J. W., Thompson, E. W., Eggers, S., Doyle, S. R. & Dobrovic, A. Exemplary multiplex bisulfite amplicon data used to demonstrate the utility of Methpat. Gigascience 4, 55 (2015). (* Joint first author)
Leeming, M. G., Isaac, A. P., Pope, B. J., Cranswick, N., Wright, C. E., Ziogas, J., O’Hair, R. A. J. & Donald, W. A. High-resolution twin-ion metabolite extraction (HiTIME) mass spectrometry: nontargeted detection of unknown drug metabolites by isotope labeling, liquid chromatography mass spectrometry, and automated high-performance computing. Anal. Chem. 87, 4104–4109 (2015).
Khong, J. J., Wang, L. Y., Smyth, G. K., McNab, A. A., Hardy, T. G., Selva, D., Llamas, B., Jung, C.-H., Sharma, S., Burdon, K. P., Ebeling, P. R. & Craig, J. E. Differential Gene Expression Profiling of Orbital Adipose Tissue in Thyroid Orbitopathy. Invest. Ophthalmol. Vis. Sci. 56, 6438–6447 (2015).
Quek, C., Jung, C.-H., Bellingham, S. A., Lonie, A. & Hill, A. F. iSRAP – a one-touch research tool for rapid profiling of small RNA-seq data. Journal of Extracellular Vesicles 4, (2015).
Dugué, P.-A., English, D. R., MacInnis, R. J., Joo, J. E., Jung, C.-H. & Milne, R. L. The repeatability of DNA methylation measures may also affect the power of epigenome-wide association studies. Int. J. Epidemiol. 44, 1460–1461 (2015).
Li, S., Wong, E. M., Joo, J. E., Jung, C.-H., Chung, J., Apicella, C., Stone, J., Dite, G. S., Giles, G. G., Southey, M. C. & Hopper, J. L. Genetic and Environmental Causes of Variation in the Difference Between Biological Age Based on DNA Methylation and Chronological Age for Middle-Aged Women. Twin Res. Hum. Genet. 18, 720–726 (2015).
Damiano, J. A., Afawi, Z., Bahlo, M., Mauermann, M., Misk, A., Arsov, T., Oliver, K. L., Dahl, H.-H. M., Shearer, A. E., Smith, R. J. H., Hall, N. E., Mahmood, K., Leventer, R. J., Scheffer, I. E., Muona, M., Lehesjoki, A.-E., Korczyn, A. D., Herrmann, H., Berkovic, S. F. & Hildebrand, M. S. Mutation of the nuclear lamin gene LMNB2 in progressive myoclonus epilepsy with early ataxia. Hum. Mol. Genet. 24, 4483–4490 (2015).
Nguyen-Dumont, T., Hammet, F., Mahmoodi, M., Pope, B. J., Giles, G. G., Hopper, J. L., Southey, M. C. & Park, D. J. Abridged adapter primers increase the target scope of Hi-Plex. Biotechniques 58, 33–36 (2015).
Nguyen-Dumont, T., Mahmoodi, M., Hammet, F., Tran, T., Tsimiklis, H., Kathleen Cuningham Foundation Consortium for Research into Familial Breast Cancer (kConFab), Giles, G. G., Hopper, J. L., Australian Breast Cancer Family Registry, Southey, M. C. & Park, D. J. Hi-Plex targeted sequencing is effective using DNA derived from archival dried blood spots. Anal. Biochem. 470, 48–51 (2015).
Nguyen-Dumont, T., Hammet, F., Mahmoodi, M., Tsimiklis, H., Teo, Z. L., Li, R., Pope, B. J., Terry, M. B., Buys, S. S., Daly, M., Hopper, J. L., Winship, I., Goldgar, D. E., Park, D. J. & Southey, M. C. Mutation screening of PALB2 in clinically ascertained families from the Breast Cancer Family Registry. Breast Cancer Res. Treat. 149, 547–554 (2015).
Inouye, M., Dashnow, H., Raven, L.-A., Schultz, M. B., Pope, B. J., Tomita, T., Zobel, J. & Holt, K. E. SRST2: Rapid genomic surveillance for public health and hospital microbiology labs. Genome Med. 6, 90 (2014).
Severi, G., Southey, M. C., English, D. R., Jung, C.-H., Lonie, A., McLean, C., Tsimiklis, H., Hopper, J. L., Giles, G. G. & Baglietto, L. Epigenome-wide methylation in DNA from peripheral blood as a marker of risk for breast cancer. Breast Cancer Res. Treat. 148, 665–673 (2014).
Pope, B. J., Nguyen-Dumont, T., Hammet, F. & Park, D. J. ROVER variant caller: read-pair overlap considerate variant-calling software applied to PCR-based massively parallel sequencing datasets. Source Code Biol. Med. 9, 3 (2014).
Ahsan, H., …, Park, D.J., …, et al. A genome-wide association study of early-onset breast cancer identifies PFKM as a novel breast cancer gene and supports a common genetic spectrum for breast cancer at any age. Cancer Epidemiology, Biomarkers and Prevention 23, 658-669 (2014).
Park, D. J., Tao, K., Le Calvez-Kelm, F., Nguyen-Dumont, T., Robinot, N., Hammet, F., Odefrey, F., Tsimiklis, H., Teo, Z. L., Thingholm, L. B., Young, E. L., Voegele, C., Lonie, A., Pope, B. J., Roane, T. C., Bell, R., Hu, H., Shankaracharya, Huff, C. D., Ellis, J., Li, J., Makunin, I. V., John, E. M., Andrulis, I. L., Terry, M. B., Daly, M., Buys, S. S., Snyder, C., Lynch, H. T., Devilee, P., Giles, G. G., Hopper, J. L., Feng, B.-J., Lesueur, F., Tavtigian, S. V., Southey, M. C. & Goldgar, D. E. Rare mutations in RINT1 predispose carriers to breast and Lynch syndrome-spectrum cancers. Cancer Discov. 4, 804–815 (2014).
Park, D. J., Nguyen-Dumont, T., Kang, S., Verspoor, K. & Pope, B. J. Annokey: an annotation tool based on key term search of the NCBI Entrez Gene database. Source Code Biol. Med. 9, 1–9 (2014).
Feil, S. C., Ascher, D. B., Kuiper, M. J., Tweten, R. K. & Parker, M. W. Structural studies of Streptococcus pyogenes streptolysin O provide insights into the early steps of membrane penetration. J. Mol. Biol. 426, 785–792 (2014).
Bujalka, H., Koenning, M., Jackson, S., Perreau, V. M., Pope, B., Hay, C. M., Mitew, S., Hill, A. F., Lu, Q. R., Wegner, M., Srinivasan, R., Svaren, J., Willingham, M., Barres, B. A. & Emery, B. MYRF is a membrane-associated transcription factor that autoproteolytically cleaves to directly activate myelin genes. PLoS Biol. 11, e1001625 (2013).
Garcia-Closas, M., …, Park, D. J., …, et. al. Genome-wide association studies identify four ER negative-specific breast cancer risk loci. Nat. Genet. 45, 392–8, 398e1–2 (2013).
Teo, Z. L., Park, D. J., Provenzano, E., Chatfield, C. A., Odefrey, F. A., Nguyen-Dumont, T., kConFab, Dowty, J. G., Hopper, J. L., Winship, I., Goldgar, D. E. & Southey, M. C. Prevalence of PALB2 mutations in Australasian multiple-case breast cancer families. Breast Cancer Res. 15, R17 (2013).
Joo, J. E., Wong, E. M., Baglietto, L., Jung, C.-H., Tsimiklis, H., Park, D. J., Wong, N. C., English, D. R., Hopper, J. L., Severi, G., Giles, G. G. & Southey, M. C. The use of DNA from archival dried blood spots with the Infinium HumanMethylation450 array. BMC Biotechnol. 13, 23 (2013).
Pope, B. J., Nguyen-Dumont, T., Odefrey, F., Hammet, F., Bell, R., Tao, K., Tavtigian, S. V., Goldgar, D. E., Lonie, A., Southey, M. C. & Park, D. J. FAVR (Filtering and Annotation of Variants that are Rare): methods to facilitate the analysis of rare germline genetic variants from massively parallel sequencing datasets. BMC Bioinformatics 14, 65 (2013).
Teo, Z. L., Provenzano, E., Dite, G. S., Park, D. J., Apicella, C., Sawyer, S. D., James, P. A., Mitchell, G., Trainer, A. H., Lindeman, G. J., Shackleton, K., Cicciarelli, L., kConFab, Buys, S. S., Andrulis, I. L., Mulligan, A. M., Glendon, G., John, E. M., Terry, M. B., Daly, M., Odefrey, F. A., Nguyen-Dumont, T., Giles, G. G., Dowty, J. G., Winship, I., Goldgar, D. E., Hopper, J. L. & Southey, M. C. Tumour morphology predicts PALB2 germline mutation status. Br. J. Cancer 109, 154–163 (2013).
COMPLEXO, Southey, M. C., Park, D. J., …, et, al. COMPLEXO: identifying the missing heritability of breast cancer via next generation collaboration. Breast Cancer Res. 15, 402 (2013).
Nguyen-Dumont, T., Pope, B. J., Hammet, F., Southey, M. C. & Park, D. J. A high-plex PCR approach for massively parallel sequencing. Biotechniques 55, 69–74 (2013).
Nguyen-Dumont, T., Pope, B. J., Hammet, F., Mahmoodi, M., Tsimiklis, H., Southey, M. C. & Park, D. J. Cross-platform compatibility of Hi-Plex, a streamlined approach for targeted massively parallel sequencing. Anal. Biochem. 442, 127–129 (2013).
Nguyen-Dumont, T., Teo, Z. L., Pope, B. J., Hammet, F., Mahmoodi, M., Tsimiklis, H., Sabbaghian, N., Tischkowitz, M., Foulkes, W. D., Kathleen Cuningham Foundation Consortium for research into Familial Breast cancer (kConFab), Giles, G. G., Hopper, J. L., Australian Breast Cancer Family Registry, Southey, M. C. & Park, D. J. Hi-Plex for high-throughput mutation screening: application to the breast cancer susceptibility gene PALB2. BMC Med. Genomics 6, 48 (2013).
Sadedin, S. P., Pope, B. & Oshlack, A. Bpipe: a tool for running and managing bioinformatics pipelines. Bioinformatics 28, 1525–1526 (2012).
Mahmood, K., Webb, G. I., Song, J., Whisstock, J. C. & Konagurthu, A. S. Efficient large-scale protein sequence comparison and gene matching to identify orthologs and co-orthologs. Nucleic Acids Res. 40, e44 (2012).
Reboul, C. F., Mahmood, K., Whisstock, J. C. & Dunstone, M. A. Predicting giant transmembrane β-barrel architecture. Bioinformatics 28, 1299–1302 (2012).
Reumann, M., Makalic, E., Goudey, B. W., Inouye, M., Bickerstaffe, A., Bui, M., Park, D. J., Kapuscinski, M. K., Schmidt, D. F., Zhou, Z., Qian, G., Zobel, J., Wagner, J. & Hopper, J. L. Supercomputing enabling exhaustive statistical analysis of genome wide association study data: Preliminary results. Conf. Proc. IEEE Eng. Med. Biol. Soc. 2012, 1258–1261 (2012).
Siddiq, A., …, Park, D. J., …, et. al. A meta-analysis of genome-wide association studies of breast cancer identifies two novel susceptibility loci at 6q14 and 20q11. Hum. Mol. Genet. 21, 5373–5384 (2012).
Ghoussaini, M., …, Park, D. J., …, et. al. Genome-wide association analysis identifies three new breast cancer susceptibility loci. Nat. Genet. 44, 312–318 (2012).
Hein, R., …, Park, D. J., …, et. al. Comparison of 6q25 breast cancer hits from Asian and European Genome Wide Association Studies in the Breast Cancer Association Consortium (BCAC). PLoS One 7, e42380 (2012).
Stevens, K.N., …, Park, D.J., …, et al. 19p13.1 is a triple-negative-specific breast cancer susceptibility locus. Cancer Research 72, 1795-1803 (2012).
Park, D. J., Lesueur, F., Nguyen-Dumont, T., Pertesi, M., Odefrey, F., Hammet, F., Neuhausen, S. L., John, E. M., Andrulis, I. L., Terry, M. B., Daly, M., Buys, S., Le Calvez-Kelm, F., Lonie, A., Pope, B. J., Tsimiklis, H., Voegele, C., Hilbers, F. M., Hoogerbrugge, N., Barroso, A., Osorio, A., Breast Cancer Family Registry, Kathleen Cuningham Foundation Consortium for Research into Familial Breast Cancer, Giles, G. G., Devilee, P., Benitez, J., Hopper, J. L., Tavtigian, S. V., Goldgar, D. E. & Southey, M. C. Rare mutations in XRCC2 increase the risk of breast cancer. Am. J. Hum. Genet. 90, 734–739 (2012).
Lawrence, S. L., Feil, S. C., Holien, J. K., Kuiper, M. J., Doughty, L., Dolezal, O., Mulhern, T. D., Tweten, R. K. & Parker, M. W. Manipulating the Lewis antigen specificity of the cholesterol-dependent cytolysin lectinolysin. Front. Immunol. 3, 330 (2012).
Ho, H. K., Gange, G., Kuiper, M. J., Ramamohanarao, K. BetaSearch: a new method for querying β-residue motifs. BMC Res. Notes 5, 391 (2012).
Roberts, J. A., Kuiper, M. J., Thorley, B. R., Smooker, P. M. & Hung, A. Investigation of a predicted N-terminal amphipathic α-helix using atomistic molecular dynamics simulation of a complete prototype poliovirus virion. J. Mol. Graph. Model. 38, 165–173 (2012).
Miller, K. A., Williams, L. H., Rose, E., Kuiper, M., Dahl, H.-H. M. & Manji, S. S. M. Inner ear morphology is perturbed in two novel mouse models of recessive deafness. PLoS One 7, e51284 (2012).
Thompson, E. R., Doyle, M. A., Ryland, G. L., Rowley, S. M., Choong, D. Y. H., Tothill, R. W., Thorne, H., kConFab, Barnes, D. R., Li, J., Ellul, J., Philip, G. K., Antill, Y. C., James, P. A., Trainer, A. H., Mitchell, G. & Campbell, I. G. Exome sequencing identifies rare deleterious mutations in DNA repair genes FANCC and BLM as potential breast cancer susceptibility alleles. PLoS Genet. 8, e1002894 (2012).PLoS One 7, e51284 (2012).
Pope, B. J., Fitch, B. G., Pitman, M. C., Rice, J. J. & Reumann, M. Performance of hybrid programming models for multiscale cardiac simulations: preparing for petascale computation. IEEE Trans. Biomed. Eng. 58, 2965–2969 (2011).
Pope, B. J., Fitch, B. G., Pitman, M. C., Rice, J. J. & Reumann, M. Petascale computation performance of lightweight multiscale cardiac models using hybrid programming models. Conf. Proc. IEEE Eng. Med. Biol. Soc. 2011, 433–436 (2011).
Song, J., Tan, H., Boyd, S. E., Shen, H., Mahmood, K., Webb, G. I., Akutsu, T., Whisstock, J. C. & Pike, R. N. Bioinformatic approaches for predicting substrates of proteases. J. Bioinform. Comput. Biol. 9, 149–178 (2011).
Park, D. J., Southey, M. C., Giles, G. G. & Hopper, J. L. No evidence of MMTV-like env sequences in specimens from the Australian Breast Cancer Family Study. Breast Cancer Res. Treat. 125, 229–235 (2011).
Park, D. J. Lariat-dependent nested PCR for flanking sequence determination. Methods Mol. Biol. 687, 43–55 (2011).
Park, D. J., Odefrey, F. A., Hammet, F., Giles, G. G., Baglietto, L., Abcfs, Mccs, Hopper, J. L., Schmidt, D. F., Makalic, E., Sinilnikova, O. M., Goldgar, D. E. & Southey, M. C. FAN1 variants identified in multiple-case early-onset breast cancer families via exome sequencing: no evidence for association with risk for breast cancer. Breast Cancer Res. Treat. 130, 1043–1049 (2011).
Park, D. J., Southey, M. C., Gilts, G. G. & Hopper, J. L. Response to’Presence of MMTV-like env gene sequences in human breast cancer’. Breast Cancer Res. Treat. 125, (2011).
Veldhuis, N. A., Kuiper, M. J., Dobson, R. C. J., Pearson, R. B. & Camakaris, J. In silico modeling of the Menkes copper-translocating P-type ATPase 3rd metal binding domain predicts that phosphorylation regulates copper-binding. Biometals 24, 477–487 (2011).
Manji, S. S. M., Miller, K. A., Williams, L. H., Andreasen, L., Siboe, M., Rose, E., Bahlo, M., Kuiper, M. & Dahl, H.-H. M. An ENU-induced mutation of Cdh23 causes congenital hearing loss, but no vestibular dysfunction, in mice. Am. J. Pathol. 179, 903–914 (2011).
Song, J., Tan, H., Shen, H., Mahmood, K., Boyd, S. E., Webb, G. I., Akutsu, T. & Whisstock, J. C. Cascleave: towards more accurate prediction of caspase substrate cleavage sites. Bioinformatics 26, 752–760 (2010).
Mahmood, K., Konagurthu, A. S., Song, J., Buckle, A. M., Webb, G. I. & Whisstock, J. C. EGM: encapsulated gene-by-gene matching to identify gene orthologs and homologous segments in genomes. Bioinformatics 26, 2076–2084 (2010).
Southey, M. C., Teo, Z. L., Dowty, J. G., Odefrey, F. A., Park, D. J., Tischkowitz, M., Sabbaghian, N., Apicella, C., Byrnes, G. B., Winship, I., Baglietto, L., Giles, G. G., Goldgar, D. E., Foulkes, W. D., Hopper, J. L. & kConFab for the Beast Cancer Family Registry. A PALB2 mutation associated with high risk of breast cancer. Breast Cancer Res. 12, R109 (2010).
Park, D. J. PCR Protocols. (Humana Press, 2010).
We are the inventors of Hi-Plex Sequencing (www.hiplex.org), integrating bioinformatic and molecular biological innovations to enable a PCR-based target-enrichment system (e.g., for massively parallel sequencing) unrivalled in terms of simplicity, accuracy and cost. Hi-Plex is suitable for an extensive range of clinical and research applications and is complemented by software for primer design (contact us for more information) and variant calling (see below).
Team members have contributed to the development of the following published software:
Cpipe: a clinical variant calling pipeline, used by the Melbourne Genomics Health Alliance, https://github.com/MelbourneGenomics/cpipe
UNDR-ROVER: a variant calling tool for targeted DNA sequencing, https://github.com/bjpop/undr_rover
ROVER: a variant calling tool for targeted DNA sequencing, https://github.com/bjpop/rover
FAVR: a rare variant filtering and annotation tool, https://github.com/bjpop/favr
Annokey: gene-based search for key-terms in the NCBI gene database and associated PubMed abstracts, https://github.com/bjpop/annokey
HiTIME: a software tool for detecting twin ion signals in high resolution liquid chromatography mass spectrometry (LCMS) data, https://github.com/bjpop/HiTIME
Methpat: a program for summarising and visualising CpG methylation patterns, https://github.com/bjpop/methpat
Burgene. an interactive web-server for prioritising genes by comparing burden of predicted pathogenic mutation in cases compared to a reference population (ExAC and gnomAD). burgene.org
Predictein. Structure and function prediction of proteomes. http://www.predictein.org/
Dovex. A web based tool to quickly provide an interactive overview and enable quick exploration of datasets, https://github.com/supernifty/dovex
Bionitio. A template for command line bioinformatics tools in various programming languages. The purpose of the tool is to provide an easy-to-understand working example that is built on best-practice software engineering principles. It can be used as a basis for learning and as a solid foundation for starting new projects. https://github.com/bionitio-team/bionitio
Team members have been, or are currently, investigators on the following grants:
NHMRC project grant APP1125269 “Expanding diagnostic approaches for Lynch syndrome”, $1,269,355, 2017 (3 years), CIE Pope.
NHMRC project grant APP1125179 “A functional assay to classify genetic variants in Lynch syndrome”, $368,194.80 AUD, 2016 (2 years). CIA Park, AI Pope.
Cancer Council Victoria (CCV) project grant APP1066612 “Mouse phenotype-driven breast cancer risk gene discovery”, $200,000 AUD, 2014 (2 years). CIA Park, CIC Pope.
Cancer Australia “High risk genes for childhood cancer: using massively parallel sequencing to identify cancer susceptibility”, $200,000 AUD, 2014 (2 years). CIE Park, CIH Pope.
Cancer Australia “High Risk Genes for Lobular Breast Cancer”, $300,000 AUD, 2013 (3 years). CIC Park, AI Pope.
NHMRC project grant APP1025145 “Identifying missing heritability in breast cancer”, $446,000 AUD, 2012 (3 years). CIC Park.
NHMRC project grant APP1028280, “High risk genes for prostate cancer”, $561,000 AUD, 2012 (3 years). CIC Park.
National Health and Medical Research Council (NHMRC) project grant APP1025879 “Massively parallel sequencing and PCR optimised for DNA-based diagnostics and discovery”, $196,544 AUD, 2012 (2 years). CIA Park, CIB Pope.
Team members are currently supervising, or have supervised, the following research students:
Jack Kaiser: Honours, Deakin University, 2016. “Computational modelling of the HIV assembly lattice”. Supervised by Michael Kuiper.
Kamran Dilmir: MSc Bioinformatics, The University of Melbourne, 2016. Supervised by Khalid Mahmood.
Edmund Lau: UROP, 2015. VLSCI intern 2016. “Multiplex PCR primer design software”. Supervised by Bernard Pope and Daniel Park.
Sean Cartwright: Research student, Elizabeth Blackburn School of Science, 2015. “How does the New Delhi metallo-beta-lactamase 1 (NDM-1) protein influence resistance to penicillin?”. Mentored by Michael Kuiper.
Roger Li: UROP, 2014. “ROVER variant calling software”. Supervised by Bernard Pope and Daniel Park.
Luke Zappia: VLSCI intern, 2014. “Hi-TIME twin ion detection software”. Supervised by Bernard Pope and Andrew Isaac.
Jumana Yousef: VLSCI intern, 2014. Supervised by Chol-Hee JUNG and Eric Joo.
Ben Harper: Research student, Elizabeth Blackburn School of Science, 2014. “Simulation of Prion proteins”. Mentored by Michael Kuiper.
Luke Shillabeer: VLSCI intern, 2013. “Multiplex PCR primer design software”. Supervised by Bernard Pope and Daniel Park.
Yu Wan: MSc Bioinformatics, The University of Melbourne, 2013. Supervised by Chol-Hee JUNG.
Kian Ho: PhD, The University of Melbourne, 2014. “Computational substructure querying and topology prediction of the beta-sheet”. Supervised by Michael Kuiper.
Sori Kang: AMSI-VLSCI intern, 2012. “Multiplex PCR primer design software and the Annokey gene prioritisation tool”. Supervised by Bernard Pope and Daniel Park.
David Edwards: MSc Bioinformatics, The University of Melbourne, 2012. “A pipeline for microbial genomics”. Supervised by Bernard Pope and Kat Holt.
Camelia Quek: PhD, The University of Melbourne, 2012. “Defining the roles of long and small transcriptomes in neurodegenerative diseases”. Co-supervised/mentored by Chol-hee JUNG.
2019 update: This project continued to progress well in 2019, with Khalid Mahmood sharing his expertise with the group. Several significant collaborations have developed across several projects in the laboratory. The focus of these collaborations has been to use genomics and associated clinical data to characterise CRCs to improve screening and diagnostics strategies for patients. […]
2019 update: This work progressed well in 2019, with Gayle Philip and Dieter Bulach sharing their expertise with the Prof van Oppen’s team. Along with conducting her own analysis of high-throughput data generated by the lab, Gayle has been upskilling members of the lab to be able to perform their own analyses. This has included […]
2019 update: Chol Hee Jung has been carrying out the quality control and processing of Australian data and the identification and analysis of genomic variants using various analysis pipelines on this major research project. He also handled the local management of data and organised data sharing with international collaborators. Further funding Preliminary investigations have contributed […]
Researchers across the Parkville Precinct and beyond now have a simpler way to run their data analysis pipelines on multiple computing platforms thanks to recent developments in the Portable Pipelines Project. Over 2019, our team of experts across WEHI, PeterMac and Melbourne Bioinformatics built Janis, a new Python framework for building and running workflows. Janis […]
Large datasets generated by researchers using liquid chromatography-mass spectrometry to identify unknown drug metabolites can now be processed more quickly and efficiently by using HiTIME, a novel memory efficient and scalable parallelisation algorithm which allows timely processing on commodity computing hardware. Computer scientists and chemists from the University of Melbourne and University of NSW have […]
Recently in our Human Genomics group we have been reflecting on the complex problems which can arise when performance metrics of genetic variant effect prediction algorithms used in clinical genomics and research are confounded by circularity and error propagation. Our findings have now been published online: Mahmood, K., Jung, C.H., Philip, G., Georgeson, P., Chung, J., Pope, […]
Hi-Plex was developed by our Molecular Biologist, Assoc Prof Daniel Park and Computer Scientist, Dr Bernard Pope, co-leads of our Human Genomics Group at Melbourne Bioinformatics, to simplify processes and reduce costs on projects needing targeted sequencing of panels of genes across large numbers of specimens. It brings greater efficiency and accuracy to all such research […]
Hi-Plex was developed by our Molecular Biologist, Assoc Prof Daniel Park and Computer Scientist, Assoc Prof Bernard Pope, co-leads of our Human Genomics Group at Melbourne Bioinformatics, to simplify processes and reduce costs on projects needing targeted sequencing of panels of genes across large numbers of specimens. It brings greater efficiency and accuracy to all such research […]