Jon has focussed his talents on bioinformatics in a research setting, motivated by introducing innovations which will change the way biologists analyse data. He has gained relevant experience on the most up-to-date single cell RNA-seq analyses, spatial transcriptomics analyses, multi-omics analyses and other bioinformatics skills. He applied a h3k27me3-based chromatin-impacting algorithm on a set of HiPSC scRNA-seq data and discovered important regulatory genes in cardiac development and also developed an R shiny application to enable user-friendly analysis on this cardiac or any custom datasets, and allow more accurate clustering of single cells using chromatin-enhanced RNA analysis approach. Augmenting Jon’s extensive bioinformatic knowledge is his wet lab experience, most recently in culturing human induced pluripotent stem cells into live beating cardiac tissues in vitro. Thus, Jon has the skill of being able to seamlessly amalgamate and exploit both wet and dry lab skills and to pass that understanding on to the biological studies in the collaborative research projects. He has recently developed a python package using a hidden state machine learning model to identify genetically distinct samples within a mixed population, without the need to know the sample genotypes prior to mixing. His work has been published as “Genotype-free demultiplexing of pooled single-cell RNA-seq” on Genome Biology.

Researcher biography

Jon obtained a Bachelor degree in Electronic Engineering from Shanghai Jiaotong University in China and his Master of Bioinformatics from UQ. He has been involved in the field of software engineering for over 15 years, during which time he has worked in global consulting firms including Accenture and Capgemini, focusing on enterprise software development and deployment. He has experience with a broad range of data analysis and data mining softwares such as SAP BI, Oracle BIEE, and SAS.  He is proficient in a variety of different programming languages and has worked on numerous operating systems including Windows, Linux and multiple versions of Unix platforms. Jon worked as a project manager in enterprise projects before he started in science.

Featured projects Duration
Genome-wide CRISPR screening for modifiers of diverse cellular phenotypes
Genome Innovation Hub Collaborative Project (UQ infrastructure)
2019
Spatial genomics technologies to study cancer and genetic diseases in tissue contexts
Genome Innovation Hub Collaborative Project (UQ infrastructure)
2019
Understanding host-pathogen interactions through development of new co-transcriptomic single cell RNA sequencing technologies
Genome Innovation Hub Collaborative Project (UQ infrastructure)
2020
Single-cell transcriptome and chromatin profiling in plant cells
Genome Innovation Hub Collaborative Project (UQ infrastructure)
2020
Combining novel scSLAM-seq technology with 10x Genomics Chromium to track microchanges in newly synthesised RNA
Genome Innovation Hub Collaborative Project (UQ infrastructure)
2020
Simultaneous identification of RNA-chromatin interactions and transcriptomes in single cells
Genome Innovation Hub Collaborative Project (UQ infrastructure)
2020
Optimised bioinformatics and validation pipeline for genome-wide CRISPR screening data
Genome Innovation Hub Collaborative Project (UQ infrastructure)
2021
RNA velocity quantification of single-cell transcriptomics
Genome Innovation Hub Collaborative Project (UQ infrastructure)
2021
Expanding the scope of multimodal single cell sequencing
Genome Innovation Hub Collaborative Project (UQ infrastructure)
2021
HTS single cell CRISPR technology for experimental validation of population genetics and functional genomics discovery
Genome Innovation Hub Collaborative Project (UQ infrastructure)
2021
Developing new "spatial omics" capabilities
Genome Innovation Hub Collaborative Project (UQ infrastructure)
2021

Areas of research