Publications

This review describes the recent evolution in computational tools that underpin cell-cell interaction studies and discusses improvements in experimental methods enabling more high-throughput analyses. Featured on the cover of the June 2024 issue.

Here we present a computational framework to infer the spatial code underlying cell-cell interactions in a whole animal.

Here we present a novel computational tool based on tensor factorization to study how cell-cell communication changes across multiple contexts. In contrast to previous approaches, Tensor-cell2cell does not perform pairwise comparisons, and instead it considers all contexts simultaneously.

Talk for the seminars about single-cell transcriptomics applied to understand chronic diseases, organized by the Advanced Center for Chronic Diseases (ACCDiS) - Talk in Spanish.

Talk for the 1st Human Cell Atlas Latin America Single Cell RNA-seq Data Analysis Workshop.

This review describes the state-of-the-art of the analyses used for inferring cell-cell interactions and communication from gene expression.

In this work, we used constraint-based modeling to investigate the effect of the cofactor swapping of ICDH in terms of energy production, response of alternative sources of NADPH, and partitioning of fluxes between ICDH and isocitrate lyase (ICL) -a crucial bifurcation when the bacterium grows on acetate-.