Detection of drug‐drug interactions through data mining studies using clinical sources, scientific literature and social media

By Santiago Vilar, Carol Friedman, George Hripcsak. 2018

131 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Molecular Biology, Toxicology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Theory and Mathematics

1. Marinka Zitnik
2. Jure Leskovec
3. Monica Agrawal
4. William L. Hamilton
5. Kexin Huang

In Molecular Biology

1. Marinka Zitnik
2. Jure Leskovec
3. Monica Agrawal
4. William L. Hamilton
5. Petar Velickovic
6. Rex Ying
7. Stephan Günnemann
8. Xinchao Wang

In Toxicology

1. Jure Leskovec
2. Marinka Zitnik

Citations in the corpus

• Modeling polypharmacy side effects with graph convolutional networks (2018, background): “Researchers have thus attempted to collect drug-drug interactions from scientific literature and electronic medical records (Percha et al., 2012; Vilar et al., 2017), and also discovered them through network modeling, analysis of molecular target signatures (Sun et al.”