dhimmel / rephetio

Miscellaneous Content for Project Rephetio to repurpose drugs

Miscellaneous Content for Project Rephetio

This repository hosts miscellaneous content for Project Rephetio, an open project to predict new uses for existing drugs. The codebase for this project encompases a large number of repositories which are referenced in the corresponding Thinklab discussions and Zenodo archives. This repository hosts miscellaneous content, mostly visualization related.

You can learn more about and cite Project Rephetio at:

• 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
  eLife. 2017. DOI: 10.7554/eLife.26726

• Rephetio: Repurposing drugs on a hetnet
  Daniel S Himmelstein, Antoine Lizee, Christine Hessler, Leo Brueggeman, Sabrina L Chen, Dexter Hadley, Ari Green, Pouya Khankhanian, Sergio E Baranzini
  Thinklab. 2016. DOI: 10.15363/thinklab.a7

Project discussion happens primarily on Thinklab. See this issue for a drag and drop image upload location.

License

This repository is released under a CC BY 4.0 License. For reuse, please attribute either the Project Rephetio publication at https://doi.org/10.7554/eLife.26726 or this repository at https://github.com/dhimmel/rephetio, whichever is most appropriate.

rephetio's Issues

Quick image hosting for the Rephetio project #2

Since #1 is getting quite slow to load, here is another GitHub issue for uploading images related to Project Rephetio. Since Thinklab discussions don't have drag-and-drop image capability, we're using this issue as a workaround.

Quick image hosting for the Rephetio project #1

This issue is intended for hosting images with GitHub's drag & drop functionality. For example, you want to upload an image to a Thinklab discussion, but Thinklab doesn't currently have drag & drop upload. Therefore, you make a comment here to host your image.

Example GitHub issue markdown

Uploaded for http://thinklab.com/d/196#3

```markdown
![Rephetio metagraph and visualization](https://cloud.githubusercontent.com/assets/1117703/14371774/aff6b0de-fcef-11e5-9e4b-341b385abcdd.png "Rephetio metagraph and visualization")
```

![Rephetio metagraph and visualization](https://cloud.githubusercontent.com/assets/1117703/14371774/aff6b0de-fcef-11e5-9e4b-341b385abcdd.png "Rephetio metagraph and visualization")

Example GitHub issue rendering

Uploaded for http://thinklab.com/d/196#3

![Rephetio metagraph and visualization](https://cloud.githubusercontent.com/assets/1117703/14371774/aff6b0de-fcef-11e5-9e4b-341b385abcdd.png "Rephetio metagraph and visualization")

Hetnet visualization: methods to create Figure 1B

Please would like to ask which software you used to create the network in the the repo figure?

Thank you!

Neo4j Online Meetup 2017-11-30 Materials

How Project Rephetio used Neo4j to predict drug repurposing

Thursday, November 30, 2017 on YouTube. Below is the event description from Meetup:

This meetup will explore Hetionet (https://neo4j.het.io), a public Neo4j database that encodes biomedical knowledge. Hetionet v1.0 contains 47,031 nodes of 11 types and 2,250,197 relationships of 24 types.

Project Rephetio applied Hetionet to predict new uses for existing compounds, an act called drug repurposing. We'll discuss the Cypher implementation of the algorithms used for relationship prediction on hetnets (networks with multiple node and relationship types).

We'll be taking questions live during the session but if you have any before hand be sure to post them in the #neo4j-online-meetup channel of the Neo4j users slack.

We'll be hosting this session on YouTube live.

Time

09:00 PST (UTC - 8 hours)
12:00 EST (UTC - 5 hours)
17:00 UTC
18:00 CEST (UTC + 1 hour)

About The Speaker

Daniel Himmelstein, a data scientist at the University of Pennsylvania, will lead the meetup.

Previously, Daniel has discussed Project Rephetio at GraphConnect 2016 and on the Graphistania podcast.

In addition, an introductory GraphGist on the project won the Open/Government Data category of the 2016 GraphGist Challenge.