Miguel A. Ibarra-Arellano

This study compares and optimizes methods for analyzing cell type neighbor preferences in spatial tissue data, introducing COZI which outperforms existing approaches.

The paper introduces Kasumi, a method to identify persistent local patterns in spatial omics data for improved patient stratification in cancer.

micronuclAI automates micronuclei quantification to assess chromosomal instability, achieving near-human performance on cancer cell line images.

This study maps acute murine myocardial infarction with subcellular resolution, identifying a novel endocardial route of immune cell infiltration and vWF as a key mediator.

This study maps cell types and their spatial distribution in multiple sclerosis lesions to understand disease progression and identify potential therapeutic targets.