Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
A knowledge graph and a set of tools for drug repurposing
| Date | Stars |
|---|---|
| 2026-07-31 | 702 |
| 2026-08-02 | 703 |
| 2026-08-06 | 703 |
Today
— stars today
This week
— stars this week
This month
— stars this month
Momentum
0.0
growth rate 0.00%/day
# Drug Repurposing Knowledge Graph (DRKG) Drug Repurposing Knowledge Graph (DRKG) is a comprehensive biological knowledge graph relating genes, compounds, diseases, biological processes, side effects and symptoms. DRKG includes information from six existing databases including DrugBank, Hetionet, GNBR, String, IntAct and DGIdb, and data collected from recent publications particularly related to Covid19. It includes 97,238 entities belonging to 13 entity-types; and 5,874,261 triplets belonging to 107 edge-types. These 107 edge-types show a type of interaction between one of the 17 entity-type pairs (multiple types of interactions are possible between the same entity-pair), as depicted in the figure below. It also includes a bunch of notebooks about how to explore and analysis the DRKG using statistical methodologies or using machine learning methodologies such as knowledge graph embedding. <p align="center"> <img src="connectivity.png" alt="DRKG schema" width="600"> <br> <b>Figure</b>: Interactions in the DRKG. The number next to an edge indicates the number of relation-types for that entity-pair in DRKG. </p> ## Statistics of DRKG The type-wise distribution of the entities in DRKG and their original data-source(s) is shown in following table. | Entity type | Drugbank | GNBR | Hetionet | STRING | IntAct | DGIdb | Bibliography | Total Entities | |:--------------------|---------:|------:|---------:|-------:|-------:|------:|-------------:|---------------:| | Anatomy | \- | \- | 400 | \- | \- | \- | \- | 400 | | Atc | 4,048 | \- | \- | \- | \- | \- | \- | 4,048 | | Biological Process | \- | \- | 11,381 | \- | \- | \- | \- | 11,381 | | Cellular Component | \- | \- | 1,391 | \- | \- | \- | \- | 1,391 | | Compound | 9,708 | 11,961 | 1,538 | \- | 153 | 6,348 | 6,250 | 24,313 | | Disease | 1,182 | 4,746 | 257 | \- | \- | \- | 33 | 5,103 | | Gene | 4,973 | 27,111 | 19,145 | 18,316 | 16,321 | 2,551 | 3,181 | 39,220 | | Molecular Function | \- | \- | 2,884 | \- | \- | \- | \- | 2,884 | | Pathway | \- | \- | 1,822 | \- | \- | \- | \- | 1,822 | | Pharmacologic Class | \- | \- | 345 | \- | \- | \- | \- | 345 | | Side Effect | \- | \- | 5,701 | \- | \- | \- | \- | 5,701 | | Symptom | \- | \- | 415 | \- | \- | \- | \- | 415 | | Tax | \- | 215 | \- | \- | \- | \- | \- | 215 | | Total | 19,911 | 44,033 | 45,279 | 18,316 | 16,474 | 8,899 | 9,464 | 97,238 | The following table shows the number of triplets between different entity-type pairs in DRKG for DRKG and various datasources. | Entity\-type pair | Drugbank | GNBR | Hetionet | STRING | IntAct | DGIdb | Bibliography | Total interactions | |:--------------------------------------|-----------:|-------:|---------:|--------:|-------:|------:|-------------:|-------------------:| | \(Gene, Gene\) | \- | 66,722 | 474,526 | 1,496,708 | 254,346 | \- | 58,629 | 2,350,931 | | \(Compound, Gene\) | 24,801 | 80,803 | 51,429 | \- | 1,805 | 26,290 | 25,666 | 210,794 | | \(Disease, Gene\) | \- | 95,399 | 27,977 | \- | \- | \- | 461 | 123,837 | | \(Atc, Compound\) | 15,750 | \- | \- | \-
Excerpt of 14,177 characters
Read on GitHub
xiang song(charlie.song) · Amazon
22
9
Mufei Li · Georgia Institute of Technology
7
6
Da Zheng · AWS · United States
3
2
Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:7bf576e7cfc75f0b, topic:knowledge-graph, desc:knowledge graph