Marco Punta

DPCstruct classifies AlphaFold2-predicted protein structures into domain clusters, recovering known folds and identifying novel structural motifs.

This paper annotates protein families in the Unified Human Gastrointestinal Proteome using DPCfam clustering, improving family coverage over Pfam.

The paper assesses the immunogenic potential of GNAQ and GNA11 mutations in uveal melanoma using genomic and transcriptomic data, finding Q209L mutations are more immunogenic than Q209P.

DPCfam classifies protein sequences into homologous families using Density Peak Clustering, showing accuracy in aligning with Pfam families and potential for metagenomics analysis.

This study identifies resistance mutations in cancer that may have immunogenic potential, with some validated to elicit T-cell responses.

AmpliSolve improves SNV detection in deep sequencing data by estimating position-specific background noise, achieving good precision and sensitivity even at low VAFs.