Albert Dominguez Mantes

snputils provides a high-performance Python library for handling genetic variation and population structure data, improving efficiency and integration in genomic research.

The paper develops a limb organoid model to study how signaling centers direct cell fate and spatial organization during limb development.

The paper maps lipid distribution across vertebrate development using mass spectrometry imaging and reveals spatially organized metabolic circuits.

Spotiflow improves spot detection in microscopy images using deep learning, achieving subpixel accuracy and efficiency across diverse datasets.

LUNA reconstructs tissue architecture from dissociated single-cell RNA-seq data using spatial priors learned from spatial transcriptomics, validating on mouse brain datasets and disease models.

This paper introduces a statistical RNA velocity model that improves dynamical consistency and inference of cell cycle speed from scRNA-seq data.

Neural ADMIXTURE uses an autoencoder to rapidly cluster large genetic datasets, reducing computation time compared to traditional methods like ADMIXTURE.

This paper introduces Archetypal Analysis for efficient genetic clustering, showing it outperforms ADMIXTURE in speed and interpretability across human and canid datasets.