Go to content
UR Home

M.Pirkl and colleagues introduced Boolean Nested Effect Models (B-NEM) for reconstructing signalling pathways in Bioinformatics

Analyzing synergistic and non-synergistic interactions in signalling pathways using Boolean Nested Effect Models

by Martin Pirkl,

Motivation: Understanding the structure and interplay of cellular signalling pathways is one of the great challenges in molecular biology. Boolean Networks can infer signalling networks from observations of protein activation. In situations where it is difficult to assess protein activation directly, Nested Effect Models are an alternative. They derive the network structure indirectly from downstream effects of pathway perturbations. To date, Nested Effect Models cannot resolve signalling details like the formation of signalling complexes or the activation of proteins by multiple alternative input signals. Here we introduce Boolean Nested Effect Models (B-NEM). B-NEMs combine the use of downstream effects with the higher resolution of signalling pathway structures in Boolean Networks.


  1. Department of Medicine
  2. Institute of Functional Genomics