Elisa Ficarra

Self-Architecting Protein Transformers: An Empirical Study

This paper evaluates a self-architecting transformer for protein representation, showing it achieves better performance than existing models with a smaller dataset.

Integrated microRNA and proteome analysis of cancer datasets with MoPC

The paper introduces MoPc, a tool that predicts miRNA-target interactions by analyzing multi-omic data, and validates its results on cancer datasets.

Predicting gene and protein expression levels from DNA and protein sequences with Perceiver

This paper introduces Perceiver models for predicting mRNA and protein levels from DNA and protein sequences, achieving state-of-the-art performance and addressing a previously unexplored task.

Identifying the oncogenic potential of gene fusions exploiting miRNAs

This paper introduces ChimerDriver, a neural network model that classifies gene fusions as oncogenic or not using transcriptional and post-transcriptional data, achieving high accuracy and recall.

Unification of miRNA and isomiR research: the mirGFF3 format and the mirtop API

The paper introduces mirGFF3, a standardized format for miRNA/isomiR analysis, and mirtop, a tool to convert outputs into this format, enabling data sharing and comparative analysis.