The Bioinformatics Team of the Single-Cell Center focuses on computational analysis of single-cell Raman spectroscopy and multi-modal data integration. We develop algorithms and software for high-dimensional Raman data processing, feature learning, and phenotype decoding, including RamEx and VADER. The team also builds BioFlow, an LLM-assisted bioinformatics platform for workflow orchestration and structured interpretation across Raman, genomics, and single-cell sequencing data. In parallel, we develop R2R (Raman-to-RNA) models to predict transcriptomic states from Raman phenotypes, enabling cross-modal mapping between spectral signatures and gene expression programs. To support reproducibility, we maintain curated resources including microalgal genome portals and Raman spectral databases. Our applications are anchored in Nannochloropsis, integrating Raman phenotyping, genome analysis, gene editing, and single-cell sequencing to link spectral features with cellular functions.

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