I have more than 10 years of experience in Bioinformatics and Systems Medicine, as well as a 4 years of experience in the Wet Lab. In terms of methodology, I have analyzed Genomic data, such as SNP arrays and Exome-seq data, as well as Transcriptome profiles, i.e. microarrays, RNA-seq, as well as RT-qPCR data.

Furthermore, my focus has been Integrative Multi-OMICS Network Analysis, e.g. starting from pair-wise integrations such as the so called expression quantitative trait loci (eQTLs) mapping in order to link Genome variation to Transcriptome profiles, followed by re-construction of Gene Co-Expression Networks and identification of Sub-Networks (Modules) related to Phenotypic Traits or Metabolite Groups of interest.



I have experience with genotyping (SNP) array and exome sequencing (Exome-seq) data analysis, including quality control and data cleaning, SNP/indel calling and functional annotation, adjustment for confounders, imputation, association analyses and visualization. I have analyzed both, autosomal, as well as mitochondrial (MT) genetic variants.

I have performed RNA-seq, microarray and RT-qPCR transcriptome data analysis, including quality control, data filtering, normalization, differential expression analyses and visualization. Both protein coding and non-coding RNA transcripts can be analyzed at gene or isoform-level.




I also perform microbiome (mainly profiled using 16S rRNA amplicon sequencing) analyses, including quality control and pre-processing, followed taxonomic classification and down-stream analyses,
such as alpha and beta analyses, co-occurrence networks and predictive functional profiling
of the microbial communities.

My major focus is integrative systems-level network-based single and multi-OMICS data analysis, starting from pair-wise Integrations, e.g. via quantitative trait loci (QTL) mapping, linking DNA variation to transcript, protein or metabolite levels, to Multi-Dimensional Integrations, including environmental and life-stytle factors, resulting in novel Biomarker detection, biological hypothesis generation and insightful data Interpretation.

Multi-OMICS Networks