Alexander Mazein

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 develops a systems immunotoxicology workflow to model and predict adverse outcomes in immunotoxicology using a molecular interaction model and the MINERVA Platform.

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.

The paper describes the development of a computational knowledge repository, the COVID-19 Disease Map, which curates SARS-CoV-2 virus-host interaction mechanisms and provides tools for their analysis and application.

The paper evaluates the reusability and composability of manually-built RAS-RAF-MEK-ERK signaling pathway maps from three databases to improve disease model assembly.

The paper introduces SBGN bricks and their ontology to provide structured semantics for recurring molecular network concepts, enabling better annotation and construction of molecular maps.