We are pleased to present two students who are close to the end of their PhD here at AIBN to share their research with you.

Date: Thursday, 25 November

Time: 12 - 1pm

Venue: Online Via Zoom

Click here to access the free seminar.


A statistical framework for identifying distribution shapes in single-cell omics data

Mrs Malindrie Dharmaratne, Mar Group, Australian Institute for Bioengineering and Nanotechnology, UQ

We present a novel statistical framework, scShapes for identifying differential distributions in single-cell RNA-sequencing data by modelling gene expression levels using generalized linear models. While most methods for differential gene expression analysis aim to detect a shift in the mean, single cell data are driven by over-dispersion and dropouts requiring statistical distributions that can handle the excess zeros. This framework has the flexibility to adjust for covariates while explicitly modelling the variability between samples. By modelling gene expression distributions, our framework, can identify subtle variations that do not involve the change in mean. Through simulation we show that this framework is able to detect zero-inflated genes and when applied to real scRNA-seq datasets, our framework was able to identify genes and pathways linked to phenotype of interest that were not discovered through traditional analysis of transcriptomic data. Currently, we are studying whether questions about differences in distribution shape extend to other types of single cell omics data. Specifically, to study chromatin accessibility and how this might lead us to new insights on cis-regulatory elements.

Photo of Malindre DharmaratneAbout Malindrie:
Malindrie received her Bachelor of Science (Honours) degree in Statistics from the University of Colombo, Sri Lanka in 2016. In April 2019, she commenced her PhD with Associate Professor Jessica Mar at the Institute for Bioengineering and Nanotechnology, University of Queensland. She works on developing bioinformatics methods for the analysis of large-scale single-cell data using advanced statistical modelling and uses modern statistics tools to understand human disease.




Engineering of antibody fragments on yeast surfaces for dengue virus detection

Ms Fahimeh Farokhinejad, Trau Group, Australian Institute for Bioengineering and Nanotechnology, UQ. 

Dengue virus (DENV) with 4 distinct serotypes is spreading globally and is considered an emerging threat to humans. The virus is transmitted to humans by Aedes species mosquitoes. Early detection and development of a rapid diagnostic assay to screen humans or mosquitoes is required to mitigate the potential severe consequences of a DENV outbreaks. One of the most commonly used methods for dengue detection is using an immunoassay to detect NS1 (non-structural 1) protein which is present in high concentrations in mosquito saliva and in the acute stages of DENV infection in humans. Currently all diagnostic approaches for DENV detection rely on monoclonal antibodies.
In this talk, I will present bioengineered-yeast-based nano biomaterials termed nanoyeasts displaying antibody fragments against DENV NS1 as a promising alternative to monoclonal antibodies, with the potential for cost-efficient production and diagnostic deployment in a resource-limited setting for human or mosquito detection. Furthermore, engineering strategies to evolve the nano yeasts into switchable probes to i) remotely sense DENV in mosquito populations to map mosquito migration and ii) detect DENV in acute human infection will be highlighted.

Photo of Fahimeh Farokhinejad

About Fahimeh:
Fahimeh has embarked on Ph.D. journey in 2019 in Trau group. She graduated from Shiraz University of Medical Sciences (Iran) with Master of Science in Cellular and Molecular Biology-Medical Biotechnology. Her background is in the development of cell-penetrating peptides fused to recombinant proteins for protein delivery in cancer therapy. Her current research work is on protein engineering and its application in diagnostics.

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Online via Zoom