Strategy and Science

Bioinformatics research

Computational Neuroscience

This thesis, "Mixed Selectivity Across Three Parietal Areas (V6A, PE, PEc) in Macaque," investigates the neural basis of visuomotor integration in the Posterior Parietal Cortex.

The research quantified neural firing dynamics during a reaching task by employing Poisson Generalized Linear Models (GLMs) and Principal Component Analysis (PCA). This methodology generated Neural Functional Fingerprints to precisely map single-neuron activity to nine behavioral epochs.

The core finding confirms that mixed selectivity is a universal and robust coding strategy across V6A, PE, and PEc. This demonstrates a highly flexible and efficient, distributed network architecture crucial for complex sensorimotor transformations

This research at the University of Oulu focused on processing and analyzing single-cell RNA-seq (scRNA-seq) data for three cancer types (Breast, Lung, Colon). Utilizing a robust R/Bioconductor pipeline (Seurat), I implemented NicheNet analysis to map key intercellular ligand-receptor communication pathways between tumor and stromal cells.

I also co-developed the MASC scoring algorithm to quantify multi-variable biological interactions. This work delivered quantitative insights into shared molecular pathways across cancers, showcasing advanced proficiency in high-dimensional bioinformatics and complex biological data modeling.