Prof David Ascher is currently an NHMRC Investigator and Director of the Biotechnology Program at the University of Queensland. He is also Head of Computational Biology and Clinical Informatics at the Baker Institute.
David’s research focus is in modelling biological data to gain insight into fundamental biological processes. One of his primary research interests has been developing tools to unravel the link between genotype and phenotype, using computational and experimental approaches to understand the effects of mutations on protein structure and function. His group has developed a platform of over 40 widely used programs for assessing the molecular consequences of coding variants (>7 million hits/year).
Working with clinical collaborators in Australia, Brazil and UK, these methods have been translated into the clinic to guide the diagnosis, management and treatment of a number of hereditary diseases, rare cancers and drug resistant infections.
David has a B.Biotech from the University of Adelaide, majoring in Biochemistry, Biotechnology and Pharmacology and Toxicology; and a B.Sci(Hon) from the University of Queensland, majoring in Biochemistry, where he worked with Luke Guddat and Ron Duggleby on the structural and functional characterization of enzymes in the branched-chain amino acid biosynthetic pathway. David then went to St Vincent’s Institute of Medical Research to undertake a PhD at the University of Melbourne in Biochemistry. There he worked under the supervision of Michael Parker using computational, biochemical and structural tools to develop small molecules drugs to improve memory.
In 2013 David went to the University of Cambridge to work with Sir Tom Blundell on using fragment based drug development techniques to target protein-protein interactions; and subsequently on the structural characterisation of proteins involved in non-homologous DNA repair. He returned to Cambridge in 2014 to establish a research platform to characterise the molecular effects of mutations on protein structure and function- using this information to gain insight into the link between genetic changes and phenotypes. He was subsequently recruited as a lab head in the Department of Biochemistry and Molecular Biology at the University of Melbourne in 2016, before joining the Baker Institute in 2019 and the University of Queensland in 2021.
He is an Associate Editor of PBMB and Fronteirs in Bioinformatics, and holds honorary positions at Bio21 Institute, Cambridge University, FIOCRUZ, and the Tuscany University Network.
Valentin was awarded a PhD from the French National Institute of Higher Education in Agricultural Sciences and the University of Montpellier (France) in 2018. His thesis focused on methodological developments for genetic differentiation analysis in the Next Generation Sequencing era in a neutral and adaptive context. Since 2019, he works as a post-doctoral researcher at the University of Queensland in the Program in Complex Trait Genomics group under the supervision of Professor Peter Visscher. His current research focuses on studying the within and between-population genetic variation in human complex traits.
In The Ortiz-Barrientos Lab we seek to understand how natural selection drives the origin of traits and new species. We combine empirical and theoretical approaches from across multiple disciplines.
We are located in beautiful Brisbane, Australia, in the School of The Environment at The University of Queensland.
Please explore our pages to learn about research, culture, and the team of scientists that bring their passion and creativity to discovering how nature works.
Dr Sathish Periyasamy is a Research Fellow at a Queensland Brain Institute and Senior Scientist at Queensland Centre for Mental Health Research. He is currently building and focusing on Systems/Genomic Medicine and conducting research in the interface of systems genetics and psychiatry. He is involved in studying the mechanisms of (patho-)physiological processes in psychiatric disorders using a unique combination of educational experience coupled with over twenty-five years of computer programming and eleven years of computational biology experience in biomedicine. Over the past 20 years, his experience working in chemical, biological and medical domains has enabled him to focus on the interface of basic and clinical research and contribute to translational research. From 2011 to 2014, he was involved in cancer genetics research at King Abdullah International Medical Research Centre, KSA. As the bioinformatics lead, with interdisciplinary skills and expertise at the interface of computational intelligence, systems biology, and quantitative/psychiatric genetics, He has been contributing to psychiatric genetics research since 2014 in Professor Bryan Mowry’s lab.
His current research areas include:
Bioinformatics, Systems Biology and Statistical Genetics - Developing and applying GWAS, post-GWAS bioinformatics, cross-population genetic association and systems genetics approaches.
Psychiatric Genomics
Common and rare variant association studies in schizophrenia using data generated from DNA microarray and whole-exome/whole-genome sequencing technologies.
Post-GWAS bioinformatics approaches to characterise risk variants discovered in schizophrenia GWAS.
Cross-population genetic association approaches in schizophrenia.
Computational Intelligence – Developing conventional and visible deep learning models for biomedicine.
Developing genetic resources for Indigenous Oceanic populations
Dr Jian Zeng is a statistical geneticist and NHMRC Emerging Leadership Fellow at the Institute for Molecular Bioscience (IMB) at the University of Queensland (UQ). He received his PhD in animal breeding and genetics at Iowa State University and joined the Program in Complex Trait Genomics (PCTG) at UQ in 2016. His research focuses on the development and application of innovative statistical methods for estimating the genetic architecture and evolutionary signals in complex traits, identifying genetic variants, genes and other molecular intermediates associated with phenotype variation, and predicting trait phenotypes using genome sequence data. In 2019, he was awarded an NHMRC Investigator Emerging Leadership Grant to develop statistical methods and software tools for best predict an individual’s disease risk using genomic and omics data. He was an invited speaker at the prestigious Gordon Research Conference in 2019.
