Add links to RNAGlib in the DGL Readme (dmlc#3728)

* Add RNAGlib to examples and DGL-powered-projects

* Add RNAGlib to examples and DGL-powered-projects

* Add RNAGlib to examples and DGL-powered-projects

README.md

@@ -80,6 +80,7 @@ Take the survey [here](https://forms.gle/Ej3jHCocACmb49Gp8) and leave any feedba
 * GNN-RecSys: https://github.com/je-dbl/GNN-RecSys
 * Amazon Neptune ML: a new capability of Neptune that uses Graph Neural Networks (GNNs), a machine learning technique purpose-built for graphs, to make easy, fast, and more accurate predictions using graph data. https://aws.amazon.com/cn/neptune/machine-learning/
 * GNNLens2: Visualization tool for Graph Neural Networks. https://github.com/dmlc/GNNLens2
+* RNAGlib: A package to facilitate construction, analysis, visualization and machine learning on RNA 2.5D Graphs. Includes a pre-built dataset: https://rnaglib.cs.mcgill.ca 
 
 ### Awesome Papers Using DGL
 

examples/README.md

@@ -7,7 +7,9 @@ The folder contains example implementations of selected research papers related
 To quickly locate the examples of your interest, search for the tagged keywords or use the search tool on [dgl.ai](https://www.dgl.ai/).
 
 ## 2021
-
+- <a name="rnaglib"></a> Mallet et al. Learning Protein and Small Molecule binding sites in RNA molecules with 2.5D graphs. [Paper link](https://academic.oup.com/bioinformatics/article/38/5/1458/6462185?login=true)
+    - Example code: [PyTorch](https://jwgitlab.cs.mcgill.ca/cgoliver/rnaglib)
+    - Tags: semi-supervised node classification
 - <a name="hilander"></a> Xing et al. Learning Hierarchical Graph Neural Networks for Image Clustering.
     - Example code: [PyTorch](../examples/pytorch/hilander)
     - Tags: clustering