Nina Ogrinc

CPMsi: a data-driven Computational Pipeline for fast, large-scale Mass Spectrometry Imaging analysis

CPMsi is a computational pipeline that efficiently processes and integrates large-scale MSI data, enabling faster analysis and discovery of molecular patterns across tissue sections.

Image-guided alignment of consecutive multi-modal tissue slides

COAST aligns consecutive tissue sections using only spatial images, enabling unified multi-modal molecular data analysis without molecular markers or annotations.

Development of Molecular Digital Twins Based on Ambient Ionization Mass Spectrometry Imaging for Real-Time Application in Oncological Surgery

The paper develops a machine-learning pipeline using mass spectrometry imaging to create molecular digital twins for real-time oncological surgery, enabling precise tumor margin delineation and bacterial strain prediction.

Towards CNN Representations for Small Mass Spectrometry Data Classification: From Transfer Learning to Cumulative Learning

The paper develops a cumulative learning approach for classifying small mass spectrometry datasets using 1D-CNNs, achieving high accuracy across diverse biological contexts.