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Hi there 👋

I am a Lecturer and researcher in computational biology at Burnet Institute, Australia. Our group is focused on building data resources and software tools to accelerate biomedical discovery. We collaborate closely with clinicians and biologists to get the most out of their 'omics experiments. Our lab is committed to reproducibility, open science, and diversity.

I code mostly in R and bash. I'm looking to learn more about machine learning, web design and other languages used for bioinformatics including python.

Topic areas of interest:

  • Transcriptome analysis

  • Multi-omics/epigenomics

  • Enrichment analysis

  • Scientific rigour

List of scientific publications: Google Scholar and ORCID

Contact me:

  • twitter: @mdziemann

  • email: mark.ziemann Îąt gmail.com

Pronouns: he/him

Mark Ziemann's Projects

2dpw4liam icon 2dpw4liam

Two dimensional pathway analysis of mouse RNA-seq data

5pillars icon 5pillars

Five pillars of computational reproducibility

android_toy icon android_toy

Playing around with android studio and using camera

bistro2 icon bistro2

pipeline for targeted bisulfite PCR amplicon sequencing

blinder icon blinder

The web-based document blinding assistant

cbmeth icon cbmeth

analysis of the CB methylation dataset

cistro_gmt icon cistro_gmt

enabling pathway analysis of curated chip-seq data

coex icon coex

Coexpression to predict gene function

cryptoblog icon cryptoblog

collection of code related to analysis of crypto market data

dee2 icon dee2

Digital Expression Explorer 2 (DEE2): a repository of uniformly processed RNA-seq data

dee2_gene_signatures icon dee2_gene_signatures

A resource of gene expression signatures derived from the DEE2 dataset (http://dee2.io)

dftd icon dftd

Tasmanian devil facial tumour isolates DFTD1 and DFTD2 transcriptome profiling

dna_mappers icon dna_mappers

Code to accompany https://www.biorxiv.org/content/10.1101/053686v1.full.pdf

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