David Ascher
Lab Head
Team
Thanh-Binh Nguyen
Research Officer
Research interests: computational biology, particularly, the integrative study of proteomics, protein structures, and their functions, virtual screening.
Alex de Sa
Research Officer
Research Interests: Automated and semi-automated learning
Stephanie Portelli
Research Officer
Research interests: drug resistance in infectious and non-infectious diseases
Yoochan Myung
PhD Candidate
Project: Using graph-based signatures to guide antibody engineering and epitope identification.
Saba Ifkhar
PhD Candidate
Project: Exploring cardiotoxicity risk factors.
Bruna Moreira
PhD Candidate
Project: Machine Learning models applied to Vaccine Design and Immunotherapies
Korawich Uthayopas
PhD Candidate
Project: Predicting non-coding RNA disease associations
Joao Velloso
PhD Candidate
Project: Computational guided GPCR engineering and drug development.
Emily Yunzhuo Zhou
PhD Candidate
Project: Developing structure-based deep learning methods to predict mutation effects on proteins
Qisheng Pan
PhD Candidate
Project: Accurate characterisation of the functional effects of protein coding mutations
Ouli Xie
PhD Candidate
Project: investigation into constraints in penicillin-binding protein mutations in group A and C/G Streptococcus and predicting resistance associated mutations using genomic surveillance data
Zachary O'Brien
Researcher
Project: Application of statistical and machine learning analysis of ICU data to improve patient outcomes
John-Luis Moretti
Carlos Rodrigues
Research interests: Protein-protein interactions, Machine learning, Deep learning, Web development
Raghad Al-Jarf
Project: Using machine learning to improve our understanding, and personalizing treatment of cancer.
Azadeh Alavi
Research interests: Application of machine learning to clinical data. Image based machine learning.
Malancha Karmakar
Project: Integrating structural and epidemiological modelling to identify which Tuberculosis resistance mutations are likely to arise in a population.
Moshe Olshansky
Research interests: Statistical analysis of 'omic data
Michael Silk
Project: Using population genetic diversity to characterise the mutational tolerance of a given gene, to identify pathogenic variants and structurally and functionally important regions of the protein.
Marialena Michanetzi
Marialena did her Masters of Bioinformatics project with us in 2017-2018, looking at the structural characterisation of Mycobacterium tuberculosis streptomycin resistance variants in gidB.
Joicymara Xavier
Project: Investigation of the interaction between multiple mutations on protein stability and function.
Jiazhen Hu
Project: Detecting Abnormal Heart Sounds using Image Representations
Mi-Chi Lee
Mi-Chi did her Masters of IT with us in 2019, combining machine learning with phenotypic screening to improve drug development.
Wesley Lam
Project: Predicting activity of small molecules against neglected tropical diseases
Yangyang Long
Project: Building small molecule toxicity predictors
Ke Meng
Lee Nguyen
Project: Mapping the role of PTM's in genetic diseases
Genevieve Clarke
Michael Harper
Michael Milton
Yixuan Zhang
Project: Predicting druggable targets
Mengyuan Shen
Project: Predicting the pathogenicity and patient outcomes of BRCA1/2 mutations.
Catherine Song
Project: Structure guided prediction of VHL disease outcomes
Parth Trehan
Project: Using machine and deep learning to process medical imaging data. Building new tools for improved automated analysis and diagnosis from medical images.
Ted Airey
Structural characterisation of ALS disease mutations to predict disease progression.
Kenny Lam
Project: Predicting and optimising small-molecule pharmacokinetic properties using deep learning
Elston D'Souza
Project: Identification and characterisation of proteins under different selective pressures between ethnic populations.
Noa Levi
Sophia Muller-Dott
Amanda Albanaz
Amanda did her undergraduate and Masters of Bioinformatics with us 2016-2018 looking at the structural characterisation of ALS disease mutations to predict disease progression. She is now pursuing her PhD at the University of Ostrava, Czech Republic.
Aaron Barnard
Aaron did his undergraduate project with us in 2018 looking at mapping population variation in malaria. He is now studying medicine at Melbourne University.
Vittoria Cicaloni
Vittoria joined us in 2019 to work on the structural analysis of genetic disease causing variants. She is now completing her PhD research programme at the University of Siena.
Anna Visibelli
Anna joined us in 2019 to work on an automatic modelling pipeline. She is now completing her PhD research programme at the University of Siena.
Anjali Garg
Anjalia completed her summer internship in the group in 2019. She developed a method to predict antimicrobial peptide activity. She is now looking forward to starting her PhD in the US.
Hardik Parate
Hardik worked with the group in 2019 to develop a method to map the drugability of protein surfaces.
Lucy Barr
Megan Pat
Project: Predicting drug resistant mutations in Abl
