Irina Balaur

The paper describes the development and evaluation of an agentic framework using LLMs to explore molecular interaction maps through user-driven prototyping and testing.

The paper integrates multi-modal data to identify shared molecular dysregulation across Parkinson's disease variants, finding common transcriptomic features in glial cells and potential involvement of ROBO signalling.

The paper proposes adapting FAIR indicators to assess and improve the quality and transparency of computational models in biology.

The paper assesses the FAIRness of the MINERVA platform using the RDA FAIR Data Maturity Model, focusing on the Parkinson's Disease Map and the COVID-19 Disease Map.

The paper presents a computational framework for analyzing SARS-CoV-2-host interactions to identify drug targets and model disease mechanisms.