Michele M. Monti

PHANES provides a comprehensive, interpretable database of protein features for the human proteome, integrating sequence, structure, and expression data to support biological analysis and machine learning.

This study uses a mathematical model to show that circadian clocks in Synechococcus elongatus enhance growth by enabling proteome adjustments that avoid inefficient nighttime growth.

This paper identifies low-complexity repeats as key drivers of RNA-RNA interactions and introduces RIME, a deep learning model that outperforms traditional methods in predicting these interactions.

PRALINE is a database that catalogs proteins and RNAs in biological condensates, their interactions, and the impact of single-nucleotide variants on condensate properties.

The paper analyzes two deep mutational scanning experiments to show that protein aggregation affects molecular evolution differently in distinct cellular contexts.

The paper analyzes the structural elements of the SARS-CoV-2 genome and predicts human protein interactions, identifying conserved regions and potential host factors involved in viral replication.