CBC LABS
Bioinformatics, statistical analysis, machine learning and custom pipeline development across sequencing and multi-omics projects.
selected work
End-to-end RNA sequencing analysis including differential expression, pathway enrichment, transcript quantification and quality control, with detailed reporting focused on biologically relevant outcomes.
Selected work: Differential expression and transcriptomic analyses contributed to Fennell et al., Nature Communications (2025).
Single-cell transcriptomic analysis including cell-type annotation, clustering, pathway activity and integration of molecular features for granular biological insights.
Example dataset: Giotti et al., Cancer Discovery (2024), GSE190597.
Biomarker development and evaluation using statistical and predictive modelling, including ROC–AUC analysis and performance assessment.
Selected work: Biomarker analysis contributed to Zhang et al., Nature Communications (2024).
Causal and network-based modelling using Bayesian networks, structural equation modelling and network inference to investigate potential mechanistic relationships and generate testable hypotheses.
Example dataset:TCGA-MESO, The Cancer Genome Atlas (TCGA).
"CBC Labs brings strong expertise in bioinformatics and computational biology, combining rigorous analysis with a clear understanding of the underlying biological questions. Jan has particular strengths in transcriptomics, biomarker discovery and advanced computational modelling."
Find answers on service packages, project timelines, confidentiality, and custom solutions for advanced bioinformatics needs.
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