We’re happy to share our latest publication in Computational and Structural Biotechnology Journal:
«Machine learning to dissect perturbations in complex cellular systems»

🔗 Read the article: https://doi.org/10.1016/j.csbj.2024.04.010

In this review, we explore how machine learning (ML) is revolutionizing single-cell and multi-omics analysis—helping decode how cells respond to genetic, chemical, and environmental perturbations. From CRISPR screens to spatial transcriptomics, ML offers new strategies for mapping cellular systems and identifying causal mechanisms.

This work was a true team effort by the Computational Biology and Immuno-oncology (CBIO) group. I’m especially proud to have co-authored this with Katja Rungger, Leonie Madersbacher, and our PI Hubert Hackl.

We’d love to hear your thoughts and feedback!

#MachineLearning #SingleCell #PerturbationBiology #SpatialTranscriptomics #CRISPR #AI #Bioinformatics #CSBJ #SystemsBiology #CBIO #PhDResearch