Peer Review of Computational Drug Repositioning Based on Side-Effects Mined from Social Media

February 2016

Studysummary This study suggests that a novel computational method using side-effect data from social media might aid in drug repositioning by identifying known and potential therapeutic indications.

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Peer Review of Computational Drug Repositioning Based on Side-Effects Mined from Social Media

research Peer Review #3 of "Computational drug repositioning based on side-effects mined from social media (v0.2)"

February 2016

This study found that a new computational method using side-effect data from social media can successfully identify known and potential new drug indications for repositioning efforts.

research Peer Review #1 of "Computational drug repositioning based on side-effects mined from social media (v0.1)"

February 2016

This study developed a computational method using side-effect data from social media to identify potential new drug indications, showing that it successfully recovered known and trial indications.

research Peer Review #2 of "Computational drug repositioning based on side-effects mined from social media (v0.2)"

February 2016

This study suggests that using a new computational method to mine social media for side-effect data may enhance drug repositioning by recovering known and trial drug indications effectively.

research Peer Review #3 of "Computational drug repositioning based on side-effects mined from social media (v0.1)"

February 2016

This study describes a computational method using side-effect data from social media to identify new drug indications, suggesting it could be effective for drug repositioning.

research Peer Review #2 of "Computational drug repositioning based on side-effects mined from social media (v0.1)"

February 2016

The researchers reported that a new computational method using side-effect data from social media effectively recovers known drug indications and identifies trial indications, suggesting utility for computational drug repositioning.