Martin T. R. Kuiper

The paper develops a dynamic Boolean model to simulate psoriasis development and identifies potential drug targets by predicting interventions that mimic current treatments.

The paper uses gene expression data and logical models to simulate patient-specific responses to psoriatic stimuli and identify treatment strategies.

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

The paper models cytokine and eicosanoid signaling in psoriatic keratinocytes to identify potential therapeutic targets and mechanisms of disease.

The paper curates a comprehensive catalogue of human DNA-binding transcription factors using Gene Ontology definitions and provides access to it via an online resource.

The paper predicts drug synergies using a logical modeling framework that combines manual curation with automated parameterization, showing that automated methods can outperform manual models in some cases.

The paper introduces CausalTAB, an updated format for representing causal signaling interactions, enhancing the precision and coverage of signaling network modeling.