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research:gabe [2021/08/26 11:32] – gabe | research:gabe [2022/10/13 15:30] (current) – gabe | ||
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My research is focussed on ancestral sequence reconstruction (ASR) and how it can be used to understand the large scale evolutionary histories of protein families. In short, we take huge sets of related modern day proteins and predict what the ancestors of these proteins looked like. From here, we can take these predictions into a lab and synthesise them, essentially ' | My research is focussed on ancestral sequence reconstruction (ASR) and how it can be used to understand the large scale evolutionary histories of protein families. In short, we take huge sets of related modern day proteins and predict what the ancestors of these proteins looked like. From here, we can take these predictions into a lab and synthesise them, essentially ' | ||
- | In my PhD I was involved with the development of a novel ASR tool, Graphical Representation of Ancestral Sequence Predictions (GRASP) that allows ancestral prediction at scales of data previously unavailable - tens of thousands of sequences can now be used to improve the fidelity of our predictions. An important key finding from my work was that insertions and deletions of sequence content that confound analysis at this scale can be effectively managed and actually used to suggest novel ' | ||
My current role is within the EnzOnomy project, an ARC Discovery Project focussed on sustainable protein engineering methods to convert renewable resources into industry-relevant chemicals. We use ASR to engineer and optimise the enzymes that allow these chemicals to be produced. | My current role is within the EnzOnomy project, an ARC Discovery Project focussed on sustainable protein engineering methods to convert renewable resources into industry-relevant chemicals. We use ASR to engineer and optimise the enzymes that allow these chemicals to be produced. | ||
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+ | In my PhD I was involved with the development of a novel ASR tool, Graphical Representation of Ancestral Sequence Predictions (GRASP) that allows ancestral prediction at scales of data previously unavailable - tens of thousands of sequences can now be used to improve the fidelity of our predictions. An important key finding from my work was that insertions and deletions of sequence content that confound analysis at this scale can be effectively managed and actually used to suggest novel ' | ||
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==== Education | ==== Education | ||
- | I am finalising | + | I completed |
==== Publications | ==== Publications | ||
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==== Awards | ==== Awards | ||
+ | 2022 Best Poster – Life Sciences Queensland Bioeconomy Forum | ||
2019 / 2017 Top ranked tutor in the School of Chemistry and Molecular Biosciences \\ | 2019 / 2017 Top ranked tutor in the School of Chemistry and Molecular Biosciences \\ | ||
2019 Best Speaker (Early Career Researcher) International Conference on Cytochrome P450 \\ | 2019 Best Speaker (Early Career Researcher) International Conference on Cytochrome P450 \\ |