Mitro Miihkinen

The paper develops a computational-experimental framework to identify mutant-selective EGFR inhibitors by leveraging paired activity measurements and structural analysis.

This paper estimates the completeness of large-scale single-cell sequencing projects using ecological richness metrics applied to cellular diversity data.

This paper develops a domain-adversarial neural network to predict drug combination synergy in leukemia patients using bulk transcriptomics data, showing improved accuracy over existing methods.

The paper identifies CCT8 as a MYO10 interactor critical for filopodia functions through proteomics and functional studies in cancer cells.

The paper develops an ML-powered drug discovery pipeline to design selective CK2 inhibitors with favorable off-target profiles, achieving a 90% hit-rate.

This study characterizes and spatially annotates normal and cancer-associated colon fibroblasts using single-cell RNA-sequencing and spatial transcriptomics.

The paper investigates the three-dimensional architecture of unique focal adhesions in human pluripotent stem cells and identifies structural features linked to pluripotency maintenance.

ProLIF quantitatively measures integrin-protein interactions in proteoliposomes using flow cytometry, enabling analysis of membrane effects on protein recruitment.