title: Identifying epigenetically dysregulated pathways from pathway-pathway interaction networks.
abstract: Identification of pathways that show significant difference in activity between disease and control samples have been an interesting topic of research for over a decade. Pathways so identified serve as potential indicators of aberrations in phenotype or a disease condition. Recently, epigenetic mechanisms such as DNA methylation are known to play an important role in altering the regulatory mechanism of biological pathways. It is reasonable to think that a set of genes that show significant difference in expression and methylation interact together to form a network of pathways. Existing pathway identification methods fail to capture the complex interplay between interacting pathways.
  
  
  
  This paper proposes a novel framework to identify biological pathways that are dysregulated by epigenetic mechanisms. Experiments on four benchmark cancer datasets and comparison with state-of-the-art pathway identification methods reveal the effectiveness of the proposed approach.
  
  
  
  The proposed framework incorporates both topology and biological relationships of pathways. Comparison with state-of-the-art techniques reveals promising results. Epigenetic signatures identified from pathway interaction networks can help to advance Molecular Pathological Epidemiology (MPE) research efforts by predicting tumor molecular changes.
authors.affiliation: Department of Computer Science and Engineering, NIT Calicut, Kerala, India. Electronic address: visakh_p140056cs@nitc.ac.in.
authors.forename: R
authors.initials: R
authors.lastname: Visakh
authors.affiliation: Department of Computer Science and Engineering, NIT Calicut, Kerala, India. Electronic address: nazeer@nitc.ac.in.
authors.forename: K A
authors.initials: KA
authors.lastname: Abdul Nazeer
mesh_terms: D019295:Computational Biology / Q000379:methods*; D019175:DNA Methylation / Q000235:genetics*; D044127:Epigenesis, Genetic / Q000235:genetics*; D053263:Gene Regulatory Networks / Q000235:genetics*; D006801:Humans
keywords: Differential gene expression; Differential gene methylation; Epigenetics; Feature selection; Molecular Pathological Epidemiology; Pathway–pathway interaction network