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Timo LassmannFeilman Fellow; Head, Precision Health Research and Head, Computational Biology
Research
Pushing the boundaries of rare disease diagnostics with the help of the first Undiagnosed HackathonTimo Lassmann BSc (Hons) MSc PhD Feilman Fellow; Head, Precision Health Research and Head, Computational Biology timo.lassmann@thekids.org.au
Research
Rare disease education in Europe and beyond: time to actPeople living with rare diseases (PLWRD) still face huge unmet needs, in part due to the fact that care systems are not sufficiently aligned with their needs and healthcare workforce (HWF) along their care pathways lacks competencies to efficiently tackle rare disease-specific challenges. Level of rare disease knowledge and awareness among the current and future HWF is insufficient.
Research
A phenotype centric benchmark of variant prioritisation toolsWe hypothesised that the performance of variant prioriisation tools may vary by disease phenotype.
Research
CAGE-defined promoter regions of the genes implicated in Rett SyndromeA comprehensive picture of the regulatory regions of the three genes involved in Rett Syndrome
Research
Promoter-level expression clustering identifies time development of transcriptional regulatory cascades initiated by ERBB receptors in breast cancer cellsThe analysis of CAGE (Cap Analysis of Gene Expression) time-courses has been applied to examine the dynamics of enhancer and promoter by sequentially...
Research
CRISPR-Cas9-generated PTCHD1 2489T>G stem cells recapitulate patient phenotype when undergoing neural inductionAn estimated 3.5%-5.9% of the global population live with rare diseases, and approximately 80% of these diseases have a genetic cause. Rare genetic diseases are difficult to diagnose, with some affected individuals experiencing diagnostic delays of 5-30 years. Next-generation sequencing has improved clinical diagnostic rates to 33%-48%. In a majority of cases, novel variants potentially causing the disease are discovered.
Research
SAMStat 2: quality control for next generation sequencing dataSAMStat is an efficient program to extract quality control metrics from fastq and SAM/BAM files. A distinguishing feature is that it displays sequence composition, base quality composition and mapping error profiles split by mapping quality. This allows users to rapidly identify reasons for poor mapping including the presence of untrimmed adapters or poor sequencing quality at individual read positions.
Research
Identification of novel cerebellar developmental transcriptional regulators with motif activity analysisThe FANTOM5 cerebellum time series is a high-quality transcriptome database for functional investigation of gene regulatory networks in cerebellar development
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Bilateral murine tumor models for characterizing the response to immune checkpoint blockadeThis protocol describes bilateral murine tumor models that display a symmetrical yet dichotomous response to immune checkpoint blockade