Matteo Manica

This paper introduces LM-ABC, a language model assistant for biocatalysis that streamlines enzyme engineering workflows using natural language inputs and integrates with computational tools.

PCfun annotates protein complex function using natural language processing and machine learning, integrating word embeddings from PubMed Central articles with supervised and unsupervised methods.

The paper investigates how genomic alterations affect molecular networks in prostate cancer by integrating genomic, transcriptomic, and proteomic data from 105 samples, identifying a sub-network predictive of tumor aggressiveness and recurrence.