Understanding the genetic mechanisms that drive pesticide resistance is crucial for effective monitoring of resistance but remains challenging.

Fundamental to this challenge is the elucidation of genetic architecture, comprised of the number, location and relative effect of genes on a phenotypic trait.

Ovarian cancer poses a great threat to the community due to its high fatality rate and unsatisfactory early stage detection performance. This research provides a machine learning approach to improve the classification ability and explainability in this process to discover more reliable biomarkers.

In linguistics, the grammar is a system of rules that govern how words are combined to create coherent sentences. By having a shared understanding of words and these rules, we can construct a vast array of meaningful sentences using a finite set of words.

Biological datasets are typically diverse, often sparse and require specific expertise to interpret and preprocess or annotate before the "real analysis" begins

The last decade is a witness to the remarkable contributions of OT to machine learning.

Missense Loss-of-Function variation: increased resolution for analysis of functional constraint

Modern advances in technology have led to the generation of ever-increasing amounts of quantitative data from biological systems, ranging from gene-expression snapshots of cell populations in a tissue to geometric arrangements of atoms within a molecule. Stephen Zhang (Uni Melb / MACSYS)

Recent advances in technologies for genome sequencing have enabled the generation of valuable data to study changes in genome structural organisation that occur during evolution. Eslam Ibrahim Amin, (Bioinformatician at ABC, JCSMR)