Systems Biology Solutions

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An Integrative Systems Biology Approach for Prioritizing Biomarkers and Drug Targets in Complex Diseases

Systems biology or pathway-based data analysis approaches allow the identification of networks of biological entities that may collectively define mechanisms and phenotypes, especially as they relate to disease. Herein, we applied an integrative systems biology workflow to hypothesize clinically relevant biomarkers and drugs targets for Alzheimer’s disease.1 Our workflow included several in silico approaches that integrate the prioritization of disease gene signatures, the analysis of disease-gene pathways and networks, and the ranking of putative drug targets based on their novelty scores (i.e., evaluating complete novelty, condition novelty or evidence of early development). We foresee this workflow as a universal tool for the prioritization of drug targets and biomarkers in complex diseases including, cancer, diabetes and many neurodiseases.

In this session, we will be using MetaCore to compare and analyze the differentially expressed genes (DEGs) in 6 brain regions of Alzheimer’s disease patients calculated from the gene expression profiles reported in Gene Expression Omnibus (GEO) dataset GSE5281. Next, we will apply Causal Reasoning in MetaCore Key Pathway Advisor (MetaCore KPA) to identify upstream regulatory hubs that could be prioritized as drug targets and/or biomarkers. The gene and protein hits identified from the upstream key hub predictions and downstream enrichment analyses will be integrated and analyzed using the network building tools available in MetaCore to understand the underlying mechanisms. Finally, the prioritized hypotheses will be evaluated and putative drug targets will be ranked based on their novelty scores, using the Drug Research Advisor-Target Druggability (DRA-TD).2 At the end of this session we will be able to answer the following key questions:

  • What pathways and process networks are potentially disrupted in Alzheimer’s disease?
  • What upstream key regulatory hubs are potentially activated or inhibited in Alzheimer’s disease?
  • How to integrate results from upstream and downstream analyses to generate higher confidence, clinically-relevant hypotheses about drug targets and biomarkers?
  • How to evaluate the resulting hypotheses and score putative drug targets?
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References:
1) Hajjo, R & Willis, C. Systems biology approaches to omics data analysis in complex diseases. 253rd Am Chem Soc (ACS) Natl Meet (April 2-6, San Francisco) 2017, Abst BIOT 461. 
2) Drug research Advisor, https://projectne.thomsonreuters.com/dra/, 2017.

 

AN UPSTREAM AND DOWNSTREAM SYNERGISTIC APPROACH TO OMICS DATA ANALYSIS USING KEY PATHWAY ADVISOR

  • This webinar will discuss recent trends in bioinformatics approaches to systems and network biology with an additional focus on how biologists use the Key Pathway Advisor (KPA) to analyze and interpret OMICs data. In particular, the root causes of molecular changes in the data along with relationships to prior disease and competitive scientific knowledge will be presented using the KPA analytics.
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