Integrative network-based approaches for modeling human disease

Muhammad Ali

Research output: ThesisDoctoral ThesisExternal prepared

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This thesis provides an overview of recent advances in the field of computational modeling of cellular systems, its major strengths, and limitations. We present various computational network-based approaches that integrate information from different regulatory levels to understand the mechanisms behind the onset and progression of multifactorial human disorders. For example, we report INTREGNET, a computational method for systematically identifying minimal sets of transcription factors (TFs) that can induce desired cellular transitions with increased efficiency. Furthermore, we introduce a novel integrative network-based approach for ranking Alzheimer’s disease (AD)-associated functional genetic and epigenetic variation. We also showed that particular pathways, such as sphingolipids (SL) function, are significantly dysregulated in AD. In-depth integrative analysis of these SL-related genes reveals their potential as biomarkers and for SL-targeted drug development for AD.
Original languageEnglish
Awarding Institution
  • Maastricht University
  • Kleinjans, J., Supervisor
  • van den Hove, Daniel, Co-Supervisor
  • Pishva, E., Co-Supervisor, External person
Award date30 Aug 2019
Place of PublicationMaastricht
Publication statusPublished - 2019


  • Gene regulatory networks
  • computational disease modeling
  • Integrative analysis
  • Cellular reprogramming
  • Epigenetic systems biology
  • Drug discovery

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