Project Rephetio & systematic prediction of antiepileptic drugs

Presented on January 30, 2017 to Blackfynn by

  • Daniel Himmelstein
    @dhimmel, daniel.himmelstein@gmail.com
  • Pouya Khankhanian
    pouya.khankhanian@uphs.upenn.edu

Slides online at slides.com/dhimmel/blackfynn

  • Hetnet of biology designed for drug repurposing
     
  • ~50 thousand nodes
    11 types (labels)
     
  • ~2.25 million relationships
    24 types
     
  • integrates 29 public resources
    knowledge from millions of studies
     
  • the hardest part:
    licensing of publicly available data

Hetionet v1.0

Visualizing Hetionet v1.0

https://neo4j.het.io/browser/

https://github.com/dhimmel/hetionet

Future: all biomedical knowledge in a single network

https://github.com/greenelab/snorkeling

  • Teach computers how to read the literature and extract knowledge.
     
  • Continuously and automatically refine and grow the hetnet.
     
  • Free from any legal restrictions on reuse. 

Project Rephetio: drug repurposing predictions

  • Hetionet v1.0 contains:
    • 1,538 connected compounds
    • 136 connected diseases
    • 209,168 compound–disease pairs
    • 755 treatments
  • 1,206 compound–disease metapaths with length ≤ 4
  • machine learning classifier
  • predict the probability of treatment for all 209,168 compound–disease pairs (het.io/repurpose)
  • Project online at thinklab.com/p/rephetio

Systematic integration of biomedical knowledge prioritizes drugs for repurposing
Daniel S Himmelstein, Antoine Lizee, Christine Hessler, Leo Brueggeman, Sabrina L Chen, Dexter Hadley, Ari Green, Pouya Khankhanian, Sergio E Baranzini
bioRxiv. 2016. DOI: 10.1101/087619

Does bupropion treat nicotine dependence?

  • Bupropion was first approved for depression in 1985
     
  • In 1997, bupropion was approved for smoking cessation
     
  • Can we predict this repurposing from Hetionet? The prediction was:

Compound–causes–SideEffect–causes–Compound–treats–Disease

Compound–binds–Gene–binds–Compound–treats–Disease

Compound–binds–Gene–associates–Disease

Compound–binds–Gene–participates–Pathway–participates–Disease

Epilepsy predictions

(browse all predictions at het.io/repurpose)

Discuss at thinklab.com/d/224

Evaluating the top 100 epilepsy predictions

Which target genes supported the top epilepsy predictions?

Online at thinklab.com/d/230#11

https://github.com/cognoma/cognoma

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