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Timo Lassmann BSc (Hons) MSc PhD Feilman Fellow; Head, Precision Health Research and Head, Translational Intelligence timo.lassmann@thekids.org.au

Clinical deep phenotyping and phenotype annotation play a critical role in both the diagnosis of patients with rare disorders as well as in building computationally-tractable knowledge in the rare disorders field.

Genomic sequencing in congenital heart disease (CHD) patients often discovers novel genetic variants, which are classified as variants of uncertain significance (VUS). Functional analysis of each VUS is required in specialised laboratories, to determine whether the VUS is disease causative or not, leading to lengthy diagnostic delays.

Feilman Fellow; Head, Precision Health Research and Head, Translational Intelligence

We have started a project utilising whole genome sequencing of undiagnosed children living in WA to provide a definitive diagnosis. A major challenge here is that the role and functions of the inter-genic regions of our genome (the remaining 98%) are relatively poorly understood.

We are made up of hundreds of different cell types carrying out a diverse range of functions essential for organism survival. All the information required to specify the morphology, function and response to stimuli of these cells is encoded in identical copies of the genome. The process of gene regu

Current technologies to understand which genes are turned on or off only work on large amounts of biological samples. As a consequence all measurements we receive represent averages across multiple cell types present in the sample. The situation is comparable to studying the contents of a bowl of fr

The Kids Research Institute Australia congratulates Prof Gareth Baynam and Dr Timo Lassmann on their grant over three years from the McCusker Charitable Foundation.

Platinum-based chemotherapy in combination with anti-PD-L1 antibodies has shown promising results in mesothelioma. However, the immunological mechanisms underlying its efficacy are not well understood and there are no predictive biomarkers to guide treatment decisions.

A robust understanding of the cellular mechanisms underlying diseases sets the foundation for the effective design of drugs and other interventions. The wealth of existing single-cell atlases offers the opportunity to uncover high-resolution information on expression patterns across various cell types and