Victor Eduardo Nieto Caballero

PIANO: Probabilistic Inference Autoencoder Networks for multi-Omics enables robust generative modeling of gene expression and scales single-cell integration to 100 million cells

PIANO integrates single-cell data across species and modalities, models gene expression, and scales to 100 million cells for drug perturbation analysis.

Cross-species consensus atlas of the primate basal ganglia

The paper creates a cross-species consensus atlas of primate basal ganglia cell types using multiomic data from human, macaque, and marmoset, identifying 61 conserved cell types and a novel hybrid medium spiny neuron type.

Fast Optimization of Robust Transcriptomics Embeddings using Probabilistic Inference Autoencoder Networks for multi-Omics

The paper introduces PIANO, a variational autoencoder for multi-omics integration, showing improved performance on single-species and multi-atlas datasets.