Marek Ostaszewski

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

This study uses Boolean modeling on PD cohorts to show sex-specific miRNA dysregulation affects mitochondrial biogenesis, mitophagy, and autophagy in Parkinson's disease.

This paper benchmarks four Boolean network optimization methods for gene regulatory modeling, showing distinct performance in accuracy, efficiency, and robustness to perturbations.

This study identifies 440 genes/proteins associated with atopic dermatitis severity through multi-omics analyses and highlights four with significant cross-evidence, including CEP85, which may contribute to severity via impaired phagocytosis.

This paper constructs and compares computational disease maps of ulcerative colitis and atopic dermatitis to identify shared and unique molecular mechanisms and potential therapeutic targets.

The paper presents the ISD map, an interactive resource modeling molecular mechanisms of psoriasis and atopic dermatitis, and identifies potential therapeutic targets through hypothesis generation.

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

This study uses Boolean models to analyze Parkinson's disease progression and identifies subtype-specific regulatory modules and biomolecules.

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.

This study uses Boolean modeling to analyze Parkinson's disease mechanisms, identify drug targets, and simulate treatment responses using the PD-map framework.

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 presents a web interface for a mechanistic model of the SARS-CoV-2 disease map to infer gene expression-related activities and study intervention effects.

BioKC provides a collaborative platform for curating and annotating systems biology models using SBML standards.