Events – ANU AAGI

ANU Biometrics Seminar Series

The series aims to foster knowledge exchange at the intersection of biology, statistics, computing, and data science. We hope to use this as a regular platform for the community to share their work, spark meaningful discussions and cultivate interdisciplinary collaborations. To facilitate participation from across campus, the seminars will primarily be held online via Zoom. If you are interested in organising or joining a watch party, please get in touch.

If you would like to receive notice about the seminar, please complete the short form here.

Aug 15, 2025

How will future climate change affect wheat yield and nutritional quality?
Zixiong Zhuang (Australian National University)

In the coming decades, climate change will continue to bring higher atmospheric CO2 concentrations as well as warmer air temperatures. However, the combined effects of elevated CO₂ (eCO2) and elevated temperature (eT) on wheat grain yield and nutrition quality remain largely unknown. When tested separately, eCO2 increases wheat yield and decreases grain nutritional quality, whereas eT decreases yield but with unknown effects on grain quality. To better understand the concurrent treatment of eCO2 and eT on wheat performances as per realistic future climate conditions, this talk presents early insights into one of the largest experiments to expand our knowledge in this area — testing 90 genetically diverse wheat lines under projected climate conditions by the year 2100 (800 ppm CO2 and + 5°C). This talk presents preliminary results from the first year’s experiment of this project. I outline both the traditional biometrics and high-throughput phenotyping (HTP) traits captured to explain the variations in plant responses to future climate conditions. I demonstrate analyses that support early understanding about the underlying biological mechanisms contributing to variations in wheat yield and nutrition qualities that can be studied further in future experiments.

Bio

Zixiong is a second-year PhD student at the Research School of Biology (RSB). He is supervised by Professor Danielle Way where he focuses on plant physiological responses to future climate change in Australian spring wheat lines. Zixiong completed his Master’s degree with Professor Justin Borevitz at the Australian National University. During Zixiong’s Master’s degrees, he discovered genomic structural variants using population-level long-read sequencing on wild Eucalyptus pangenomes. He joined the Way Lab in 2023, transitioning his focus from population genomics to ecophysiology and plant phenomics.

Aug 1, 2025

Novel methods for analysing single cell gene expression data
Yidi Deng (Australian National University)

This talk will introduce three novel methods we developed to address key challenges in single-cell RNA-seq (scRNA-seq) data analysis. Sincast is an imputation method that denoises scRNA-seq data to enhance the robustness of downstream statistical analyses. Its utility is highlighted through comprehensive benchmarking of cell identity against bulk transcriptomic references. StableMate is a stability-focused regression framework that identifies functional dependencies in gene expression that are either conserved or meaningfully variable across biological contexts. When applied to scRNA-seq data, StableMate enhances reproducibility and provides regulatory insights into co-expression analyses. NeighbourNet constructs cell-specific gene regulatory networks, facilitating the fine-grained characterization of gene regulatory dynamics at the single-cell level and offering a new perspective on analysing scRNA-seq through cellular variation in co-expression.

Bio

Yidi Deng is a statistical bioinformatician and new post-doctoral fellow, working with Dr Emi Tanaka to uncover genomic insights that support Australia’s grain-industry research. Yidi completed a PhD in applied statistics at the University of Melbourne, where he developed novel methods for multi-omics data integration and variable selection, aimed at deciphering gene-regulatory mechanisms in the context of developmental biology and immunology. Yidi’s overall research interests is to translate advanced statistical approaches into intuitive, practical software that biologists can easily adopt without specialized statistical or computational expertise.