Today’s personalized medicine is based on in-depth knowledge of the genetic and epigenetic repertoire of diseases and the availability of novel agents for targeting altered genes and pathways. Therefore, automated and reliable methods for analysing and interpreting this data are needed to achieve maximum explanatory power, cost and time efficiencies in medical diagnostics.
We drive the in-silico arm of the entire molecular biomarker development process from omics discovery studies, candidate signature identification, platform and matrix transfer, technical verification studies to clinical validation studies. To resolve complex disease phenotypes, we also integrate multiple omics layers from multiple tissue types and/or body fluids with imaging, clinical or exposome data.
Our expertises include:
- Study design: identification of use cases and target population, selection of target matrices and measurement platforms, cohort selection, good practices
- OMICS technologies: data processing and analysis pipelines available for whole genome (bisulfite) sequencing, RNAseq, microbiome sequencing, DNA and Protein chip data, high throughput qPCR, single-cell sequencing (coming soon). Pipeline development including GUI.
- Identification of candidate biomarker signatures: multivariate statistics, machine learning / AI, regulatory network analysis, gene set enrichment analysis, multi-omics integration, endotype discovery.
- Technology and matrix transfer: our assay design pipelines support technology transfer from screening technologies (e.g. NGS) to easy-to-use, low-tech (PCR, ELISA) assays and matrix transfer from tissue to non-invasive body fluids.
- Microbiome studies: analysis setup, data analysis and interpretation of results
- Genome assembly: generation of contigs and scaffolds, gene identification and analysis, homology analysis
- Development and validation of diagnostic signatures: validation of machine learning models based on data from clinical studies
Selected Projects
| PerSAIDs | Info | ERA PerMed |
| PIMIENTO | Info | WWTF |
| Immuniverse | www.immuniverse.eu | EU-IMI |
| BIOMAP | biomap-imi.eu | EU-IMI |
| EPITHYDIA | Info | EU - Eurostars |
| LIBIDA | Info | FFG - BRIDGE |
| ThyroidGX | Info | FFG - BRIDGE |
Selected Publications
- Heilmeier U, Hackl M, Schroeder F, Torabi S, Kapoor P, Vierlinger K, Eiriksdottir G, Gudmundsson EF, Harris TB, Gudnason V, Link TM, Grillari J, Schwartz AV. Circulating serum microRNAs including senescent miR-31-5p are associated with incident fragility fractures in older postmenopausal women with type 2 diabetes mellitus. Bone. 2022 May;158:116308. doi:10.1016/j.bone.2021.116308. Epub 2022 Jan 21. PMID: 35066213.
- Samaha E, Vierlinger K, Weinhappel W, Godnic-Cvar J, Nöhammer C, Koczan D, Thiesen HJ, Yanai H, Fraifeld VE, Ziesche R. Expression Profiling Suggests Loss of Surface Integrity and Failure of Regenerative Repair as Major Driving Forces for Chronic Obstructive Pulmonary Disease Progression. Am J Respir Cell Mol Biol. 2021 Apr;64(4):441-452. doi: 10.1165/rcmb.2020-0270OC. PMID: 33524306.
- Krainer J, Weinhäusel A, Hanak K, Pulverer W, Özen S, Vierlinger K, Pabinger S. EPIC-TABSAT: analysis tool for targeted bisulfite sequencing experiments and array-based methylation studies. Nucleic Acids Res. 2019 Jul 2;47(W1): W166-W170. doi: 10.1093/nar/gkz398. PMID: 31106358; PMCID: PMC6602470.
- Wielscher M, Vierlinger K, Kegler U, Ziesche R, Gsur A, Weinhäusel A. Diagnostic Performance of Plasma DNA Methylation Profiles in Lung Cancer, Pulmonary Fibrosis and COPD. EBioMedicine. 2015 Jul 2;2(8):929-36. doi: 10.1016/j.ebiom.2015.06.025. PMID: 26425700; PMCID: PMC4563135.
- Gröger CJ, Grubinger M, Waldhör T, Vierlinger K, Mikulits W. Meta-analysis of gene expression signatures defining the epithelial to mesenchymal transition during cancer progression. PLoS One. 2012;7(12):e51136. doi: 10.1371/journal.pone.0051136. Epub 2012 Dec 10. PMID: 23251436; PMCID: PMC3519484.
- Vierlinger K, Mansfeld MH, Koperek O, Nöhammer C, Kaserer K, Leisch F. Identification of SERPINA1 as single marker for papillary thyroid carcinoma through microarray meta analysis and quantification of its discriminatory power in independent validation. BMC Med Genomics. 2011 Apr 6;4:30. doi: 10.1186/1755-8794-4-30. PMID: 21470421; PMCID: PMC3082219.
- Aubert J, Stavridis MP, Tweedie S, O'Reilly M, Vierlinger K, Li M, Ghazal P, Pratt T, Mason JO, Roy D, Smith A. Screening for mammalian neural genes via fluorescence-activated cell sorter purification of neural precursors from Sox1-gfp knock-in mice. Proc Natl Acad Sci U S A. 2003 Sep 30;100 Suppl 1(Suppl1):11836-41. doi: 10.1073/pnas.1734197100. Epub 2003 Aug 15. PMID: 12923295; PMCID: PMC304095.
