UQ Diamantina Computational Medical Genomics Group

From wiki
Revision as of 10:41, 28 January 2018 by Shihab (Talk | contribs) (Group members)

(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
Jump to: navigation, search

We develop and apply bioinformatics methods in the context of biomedical research. Our group specialises in cancer genetics, epigenome-wide association studies, biomarker discovery, parasite whole-genome sequencing, the human microbiota, and machine learning.

Group members

  • Lutz Krause (Head)
  • Harry Oey (Postdoctoral researcher)
  • Martha Zakrzewski (Postdoctoral researcher at QIMR Berghofer Medical Research Institute)
  • Sandra Brosda (PhD student)
  • Ankit Shukla (PhD student)


Carla Proietti (QIMR Berghofer)


  • Shihab Hasan (PhD student)
  • Annika Fust (Master's student)
  • Kerstin Gravermann (Master's student)




Calypso is a powerful, yet easy to use, tool for the higher-level analysis of taxonomic information from metagenomic datasets. Consult the Calypso wiki for additional information.

Genomics Data Miner (GMine)


Easy to use online platform for mining, visualising and comparing complex biomedical research data, such as protein arrays. Consult the GMine wiki for information on using the software.


Web Server for identification of eukaryotic protein category based on protein features.


Web application for schistosome specific machine-learning identification of surface proteins and secreted peptides.


Web server for identification schistosome specific of immunoreactive proteins.

Current projects

Cancer whole-genome sequencing

We are analysing whole-genome sequening data of cancer to identify mutations, strucutral variations and copy-number variations inovlved in tumorigenesis and response to chemotherapy.

Parasite whole-genome sequencing

Parasitic infections by blood flukes (schistosomes) cause highly significant human diseases. Schistosomiasis, a chronic disease caused by Schistosoma spp., is considered by the World Health Organization as the second most socioeconomically devastating and second most common parasitic disease afflicting humans, affecting 200 million people worldwide. No vaccines are available and treatment relies on only one drug, praziquantel. The genomes of three Schistosoma species infecting humans have recently become publicly available. We are sequencing several further parasite genomes, which allows us to do a comprehensive comparative genome analysis of multiple parasites and free-living flatworms. Using bioinformatics methods, we identify genes important for host-parasite interaction and novel drug and vaccine targets. This project will provide important information for preventing and controlling human parasite infections by Schistosoma spp. affecting more than 200 million people every year. The study will provide novel insights into the evolution of human parasite genomes, identify gene functions and pathways important for the parasite-host interaction and reveal novel candidate drug and vaccine targets.

Biomarker discovery

The Bioinformatics Laboratory has a main interest in the discovery of biomarkers for disease onset, progression and personalised treatment. In collaboration with Dr. Andrew Barbour for example, we are aiming at developing biomarkers for prognosis, progression and personalised treatment in oesophageal adenocarcinoma. Heterogeneous datasets are used and integrated, including genomic variations, epigenetic modifications, gene expression changes and copy number variations. For the discovery of novel biomarkers we employ various machine learning and data-mining methods, such as Support Vector Machines, Cox models, generalised linear models, supervised and unsupervised clustering, and multivariate techniques.


The emerging field of epigenetics studies heritable changes of our genome, which switch genes on or off without altering the genetic code. Epigenetics allows organisms to dynamically respond to environmental factors like diet, stress or prenatal experiences. Failure of epigenetic regulation can lead to important diseases, including cancer and mental disorders. Examples of epigenetic changes are the methylation of cysteine or histone modifications. These marks can be studied on a whole genome scale using recently developed next-generation DNA sequencing techniques, for example by Chip-Seq or Medip-Seq. In light of the huge amounts of data generated and the size of the human genome, the analysis of Chip-Seq and Medip-Seq data poses a considerable computational challenge. The Bionformatics Laboratory is involved in several projects investigating the role of epigenetics in complex diseases, in particular cancer and psychological disorders.

The human microbiome

Our gut microbiota is an integral part of our body and increasing evidence indicates that it plays an essential role in diverse diseases such as allergies, cancer, mental illness, and metabolic and gastrointestinal disorders. While considerable efforts have been dedicated to find a cure for these diseases, their causes still remain poorly understood. The Bioinformatics Laboratory is involved in various projects investigating the role of bacteria in the development of diseases and disorders, including diabetes, obesity, gastrointestinal disorders and bacterial infections. The obtained results form a valuable basis for the development of novel treatment and prevention options and for the identification of biomarkers for disease risk. We also develop novel computational tools for mining, comparing and visualising large and complex metagenomic and 16S rDNA datasets.