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+The Synthetic Lethality resource
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+Synthetic lethal interactions (SLIs), genetic interactions in which the simultaneous inactivation of
+two genes leads to a lethal phenotype, are promising targets for therapeutic intervention in
+cancer, as exemplified by the recent success of PARP inhibitors in treating BRCA1/2-deficient
+tumors. We present SL-Cloud, an cloud based integrated resource to facilitate the prediction
+of context-specific SLIs. This resource addresses two main
+challenges related to SLI inference: the need to wrangle and preprocess large multi-omic
+datasets and the multiple comparable prediction approaches available. 
+
+SL-Cloud provides a cloud-based data access platform coupled with software and well documented 
+computational notebooks that re-implement published synthetic lethality (SL) inference algorithms to 
+facilitate novel investigation into synthetic lethality. In addition, we provide general purpose 
+functions that support these prediction workflows e.g. saving data in bigquery tables. 
+We anticipate that users can leverage the resources provided in this project 
+to conduct highly customizable analysis based on their cancer type of interest and particular context.
+
+More information of SL-Cloud can be found in the following links:
+
+- `Notebooks in MyBinder <https://mybinder.org/v2/gh/boaguilar/SL-Cloud/HEAD>`_ 
+- `GitHub Repository <https://github.com/IlyaLab/SL-Cloud/>`_ 
+- `Article describing SL-cloud <https://www.biorxiv.org/content/10.1101/2021.09.18.459450v1.abstract>`_
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