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Professor David Ascher
Professor

David Ascher

Email: 
Phone: 
+61 7 336 53991

Overview

Background

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.

Availability

Professor David Ascher is:
Available for supervision
Media expert

Research impacts

We have successfully translated our computational tools into the clinic and industry, including:

  • Clinical detection of drug resistance from whole-genome sequencing of pathogens, including Tuburculosis and Leprosy
  • Genetic counselling for rare diseases and cancers with Addenbrooke's Hospital and Brazilian Ministry of Health
  • Patient stratification within clinical trials
  • Implementation within industry drug and biologics development programs

The tools we have developed have also been widely adopted within existing academic programs including:

  • Integration of intermolecular interaction calculations using our tool Arpeggio in the PDBe, the European resource for the collection, organisation and dissemination of data on biological macromolecular structures.
  • Integration of our missense tolerance scores within the widely used VEP tool for variant characterisation.
  • Implementation of our resistance prediction tools within the London School of Hygiene & Tropical Medicine's TB-Profiler tool.

Works

Search Professor David Ascher’s works on UQ eSpace

179 works between 2008 and 2024

41 - 60 of 179 works

2022

Journal Article

kinCSM : Using graph‐based signatures to predict small molecule CDK2 inhibitors

Zhou, Yunzhuo, Al‐Jarf, Raghad, Alavi, Azadeh, Nguyen, Thanh Binh, Rodrigues, Carlos H. M., Pires, Douglas E. V. and Ascher, David B. (2022). kinCSM : Using graph‐based signatures to predict small molecule CDK2 inhibitors. Protein Science, 31 (11) e4453, 1-11. doi: 10.1002/pro.4453

kinCSM : Using graph‐based signatures to predict small molecule CDK2 inhibitors

2022

Journal Article

cardioToxCSM: a web server for predicting cardiotoxicity of small molecules

Iftkhar, Saba, de Sá, Alex G. C., Velloso, João P. L., Aljarf, Raghad, Pires, Douglas E. V. and Ascher, David B. (2022). cardioToxCSM: a web server for predicting cardiotoxicity of small molecules. Journal of Chemical Information and Modeling, 62 (20), 4827-4836. doi: 10.1021/acs.jcim.2c00822

cardioToxCSM: a web server for predicting cardiotoxicity of small molecules

2022

Journal Article

CSM‐peptides: A computational approach to rapid identification of therapeutic peptides

Rodrigues, Carlos H. M., Garg, Anjali, Keizer, David, Pires, Douglas E. V. and Ascher, David B. (2022). CSM‐peptides: A computational approach to rapid identification of therapeutic peptides. Protein Science, 31 (10) e4442, 1-9. doi: 10.1002/pro.4442

CSM‐peptides: A computational approach to rapid identification of therapeutic peptides

2022

Journal Article

Identifying the molecular drivers of ALS-implicated missense mutations

Portelli, Stephanie, Albanaz, Amanda, Pires, Douglas Eduardo Valente and Ascher, David Benjamin (2022). Identifying the molecular drivers of ALS-implicated missense mutations. Journal of Medical Genetics, 60 (5) 108798, 1-7. doi: 10.1136/jmg-2022-108798

Identifying the molecular drivers of ALS-implicated missense mutations

2022

Journal Article

VIVID: a web application for variant interpretation and visualisation in multidimensional analyses

Tichkule, Swapnil, Myung, Yoochan, Naung, Myo T., Ansell, Brendan R. E., Guy, Andrew J., Srivastava, Namrata, Mehra, Somya, Cacciò, Simone M, Mueller, Ivo, Barry, Alyssa E, van Oosterhout, Cock, Pope, Bernard, Ascher, David B and Jex, Aaron R (2022). VIVID: a web application for variant interpretation and visualisation in multidimensional analyses. Molecular Biology and Evolution, 39 (9) msac196. doi: 10.1093/molbev/msac196

VIVID: a web application for variant interpretation and visualisation in multidimensional analyses

2022

Journal Article

GASS-Metal: identifying metal-binding sites on protein structures using genetic algorithms

Paiva, Vinícius A., Mendonça, Murillo V., Silveira, Sabrina A., Ascher, David B., Pires, Douglas E. V. and Izidoro, Sandro C. (2022). GASS-Metal: identifying metal-binding sites on protein structures using genetic algorithms. Briefings in Bioinformatics, 23 (5) bbac178, 1-9. doi: 10.1093/bib/bbac178

GASS-Metal: identifying metal-binding sites on protein structures using genetic algorithms

2022

Journal Article

Sequence grammar underlying the unfolding and phase separation of globular proteins

Ruff, Kiersten M., Choi, Yoon Hee, Cox, Dezerae, Ormsby, Angelique R., Myung, Yoochan, Ascher, David B., Radford, Sheena E., Pappu, Rohit V. and Hatters, Danny M. (2022). Sequence grammar underlying the unfolding and phase separation of globular proteins. Molecular Cell, 82 (17), 3193-3208.e8. doi: 10.1016/j.molcel.2022.06.024

Sequence grammar underlying the unfolding and phase separation of globular proteins

2022

Journal Article

toxCSM: comprehensive prediction of small molecule toxicity profiles

de Sá, Alex G.C., Long, Yangyang, Portelli, Stephanie, Pires, Douglas E.V. and Ascher, David B. (2022). toxCSM: comprehensive prediction of small molecule toxicity profiles. Briefings in Bioinformatics, 23 (5) bbac337, 1-11. doi: 10.1093/bib/bbac337

toxCSM: comprehensive prediction of small molecule toxicity profiles

2022

Journal Article

Use of cluster analysis to characterise aortic stenosis phenotypes with treatable and untreatable risk

Sen, J., Pires, D., de Sá, A., Ascher, D., Wahir, S. and Marwick, T. (2022). Use of cluster analysis to characterise aortic stenosis phenotypes with treatable and untreatable risk. Heart, Lung and Circulation, 31, S44-S45. doi: 10.1016/j.hlc.2022.06.016

Use of cluster analysis to characterise aortic stenosis phenotypes with treatable and untreatable risk

2022

Journal Article

HGDiscovery: an online tool providing functional and phenotypic information on novel variants of homogentisate 1,2- dioxigenase

Karmakar, Malancha, Cicaloni, Vittoria, Rodrigues, Carlos H. M., Spiga, Ottavia, Santucci, Annalisa and Ascher, David B. (2022). HGDiscovery: an online tool providing functional and phenotypic information on novel variants of homogentisate 1,2- dioxigenase. Current Research in Structural Biology, 4, 271-277. doi: 10.1016/j.crstbi.2022.08.001

HGDiscovery: an online tool providing functional and phenotypic information on novel variants of homogentisate 1,2- dioxigenase

2022

Journal Article

CSM-Potential: mapping protein interactions and biological ligands in 3D space using geometric deep learning

Rodrigues, Carlos H. M. and Ascher, David B (2022). CSM-Potential: mapping protein interactions and biological ligands in 3D space using geometric deep learning. Nucleic Acids Research, 50 (W1), W204-W209. doi: 10.1093/nar/gkac381

CSM-Potential: mapping protein interactions and biological ligands in 3D space using geometric deep learning

2022

Journal Article

Structural landscapes of PPI interfaces

Rodrigues, Carlos H. M., Pires, Douglas E. V., Blundell, Tom L. and Ascher, David B. (2022). Structural landscapes of PPI interfaces. Briefings in Bioinformatics, 23 (4) bbac165, 1-10. doi: 10.1093/bib/bbac165

Structural landscapes of PPI interfaces

2022

Journal Article

Evaluating hierarchical machine learning approaches to classify biological databases

Rezende, Pâmela M., Xavier, Joicymara S., Ascher, David B., Fernandes, Gabriel R. and Pires, Douglas E. V. (2022). Evaluating hierarchical machine learning approaches to classify biological databases. Briefings in Bioinformatics, 23 (4) bbac216, 1-14. doi: 10.1093/bib/bbac216

Evaluating hierarchical machine learning approaches to classify biological databases

2022

Journal Article

cropCSM: designing safe and potent herbicides with graph-based signatures

Pires, Douglas E V, Stubbs, Keith A, Mylne, Joshua S and Ascher, David B (2022). cropCSM: designing safe and potent herbicides with graph-based signatures. Briefings in Bioinformatics, 23 (2) bbac042. doi: 10.1093/bib/bbac042

cropCSM: designing safe and potent herbicides with graph-based signatures

2022

Journal Article

Systematic evaluation of computational tools to predict the effects of mutations on protein stability in the absence of experimental structures

Pan, Qisheng, Nguyen, Thanh Binh, Ascher, David B and Pires, Douglas E V (2022). Systematic evaluation of computational tools to predict the effects of mutations on protein stability in the absence of experimental structures. Briefings in Bioinformatics, 23 (2) bbac025. doi: 10.1093/bib/bbac025

Systematic evaluation of computational tools to predict the effects of mutations on protein stability in the absence of experimental structures

2022

Journal Article

Known allosteric proteins have central roles in genetic disease

Abrusán, György, Ascher, David B. and Inouye, Michael (2022). Known allosteric proteins have central roles in genetic disease. PLoS Computational Biology, 18 (2) e1009806, 1-28. doi: 10.1371/journal.pcbi.1009806

Known allosteric proteins have central roles in genetic disease

2022

Journal Article

epitope3D: a machine learning method for conformational B-cell epitope prediction

da Silva, Bruna Moreira, Myung, YooChan, Ascher, David B. and Pires, Douglas E. V. (2022). epitope3D: a machine learning method for conformational B-cell epitope prediction. Briefings in Bioinformatics, 23 (1) bbab423, 1-8. doi: 10.1093/bib/bbab423

epitope3D: a machine learning method for conformational B-cell epitope prediction

2022

Journal Article

Oxidative desulfurization pathway for complete catabolism of sulfoquinovose by bacteria

Sharma, Mahima, Lingford, James P., Petricevic, Marija, Snow, Alexander J. D., Zhang, Yunyang, Järvå, Michael A., Mui, Janice W.-Y., Scott, Nichollas E., Saunders, Eleanor C., Mao, Runyu, Epa, Ruwan, da Silva, Bruna M., Pires, Douglas E. V., Ascher, David B., McConville, Malcolm J., Davies, Gideon J., Williams, Spencer J. and Goddard-Borger, Ethan D. (2022). Oxidative desulfurization pathway for complete catabolism of sulfoquinovose by bacteria. Proceedings of the National Academy of Sciences, 119 (4), e2116022119. doi: 10.1073/pnas.2116022119

Oxidative desulfurization pathway for complete catabolism of sulfoquinovose by bacteria

2022

Journal Article

CSM-carbohydrate: protein-carbohydrate binding affinity prediction and docking scoring function

Nguyen, Thanh Binh, Pires, Douglas E. V. and Ascher, David B. (2022). CSM-carbohydrate: protein-carbohydrate binding affinity prediction and docking scoring function. Briefings in Bioinformatics, 23 (1) bbab512, 1-8. doi: 10.1093/bib/bbab512

CSM-carbohydrate: protein-carbohydrate binding affinity prediction and docking scoring function

2021

Journal Article

TSMDA: Target and symptom-based computational model for miRNA-disease-association prediction

Uthayopas, Korawich, de Sá, Alex G.C., Alavi, Azadeh, Pires, Douglas E.V. and Ascher, David B. (2021). TSMDA: Target and symptom-based computational model for miRNA-disease-association prediction. Molecular Therapy - Nucleic Acids, 26, 536-546. doi: 10.1016/j.omtn.2021.08.016

TSMDA: Target and symptom-based computational model for miRNA-disease-association prediction

Funding

Current funding

  • 2023 - 2027
    Improving genetic diagnosis of autoimmune and autoinflammatory disease through an integrated multi-omics approach (MRFF 2022 GHFM - administered by ANU)
    The Australian National University
    Open grant

Supervision

Availability

Professor David Ascher is:
Available for supervision

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Supervision history

Current supervision

  • Doctor Philosophy

    Towards the accurate functional characterisation of protein coding mutations

    Principal Advisor

    Other advisors: Dr Stephanie Portelli, Dr Thanh-Binh Nguyen

  • Doctor Philosophy

    Deep Learning Algorithms for Polygenic Genotype-Phenotype Predictions and the development of genetics computation tools

    Principal Advisor

  • Doctor Philosophy

    Machine Learning for Protein Dynamics: Predicting Post-Translational Modifications and Mutation Effects

    Principal Advisor

  • Doctor Philosophy

    Using Deep Learning in Cell & Gene Therapy

    Principal Advisor

    Other advisors: Dr Thanh-Binh Nguyen, Dr Stephanie Portelli

  • Doctor Philosophy

    Protein structure guided precision medicine

    Principal Advisor

    Other advisors: Professor Phil Hugenholtz, Dr Stephanie Portelli

  • Doctor Philosophy

    Rational protein engineering and inhibition

    Principal Advisor

  • Doctor Philosophy

    Computer-aided drug design: predicting and mitigating drug toxicity

    Principal Advisor

    Other advisors: Dr Stephanie Portelli

  • Doctor Philosophy

    Improving rational antibody design using machine learning

    Principal Advisor

  • Doctor Philosophy

    Developing structure-based deep learning methods to predict mutation effects on proteins

    Principal Advisor

  • Doctor Philosophy

    Exploring Cardiotoxicity Risk Factors

    Principal Advisor

    Other advisors: Dr Thanh-Binh Nguyen

  • Doctor Philosophy

    Post-transcriptional gene regulation: towards a better understanding of pathogenesis and medical applications

    Principal Advisor

  • Doctor Philosophy

    Computational approaches to engineer and modulate G protein-coupled receptors

    Principal Advisor

  • Doctor Philosophy

    Personalising treatments for genetic diseases

    Principal Advisor

    Other advisors: Dr Stephanie Portelli

  • Doctor Philosophy

    Unravelling the Physicochemical Drivers of Biomolecular Self-Assembly though Multiscale Simulations

    Associate Advisor

    Other advisors: Dr Evelyne Deplazes, Professor Megan O'Mara

  • Doctor Philosophy

    Computational design of targeted lipid technologies

    Associate Advisor

    Other advisors: Professor Megan O'Mara

  • Doctor Philosophy

    Use of structural phylogeny and reconciliation in molecular phylogenetics

    Associate Advisor

    Other advisors: Dr Kate Bowerman, Professor Phil Hugenholtz

  • Doctor Philosophy

    Therapeutic Resolution of Inflammation in the Central Nervous System for Neuroprotection in Parkinson's Disease

    Associate Advisor

    Other advisors: Professor Avril Robertson

  • Doctor Philosophy

    Breaking the chain of inflammation through targetting NLR proteins

    Associate Advisor

    Other advisors: Professor Avril Robertson

Media

Enquiries

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