Giulio Isacchini

The paper develops a method to infer directional migration rates from ancient DNA data using time-dependent F2 statistics, revealing an ancient pan-European migration network.

The paper identifies TCR subsequence motifs associated with type 1 diabetes using deep learning and shows their enrichment in T1D individuals based on HLA risk alleles.

The paper quantitatively maps antigen specificity in immune repertoire embedding spaces, showing distinct regions for different antigen-specific sequences.

This paper introduces a two-step inference strategy for training generalized linear models of noisy interacting neurons, showing improved performance and stability across complex stimuli.