UniProt, the reference resource for proteins, provides links to DISGENET plus.
Links to DISGENET plus information on diseases associated with human genes are available to UniProt/SwissProt human protein entries.
uniprot.org/disgenetplus.com/
🗣️New release of DISGENET plus (v23)
🐁New data source: Mouse Genome Database
🧬10% increase in the number of GDAs: more than 175K new GDAs available
⚕️2.5K new diseases and phenotypes incorporated into the database
👉🏽More info at disgenetplus.com/
🗣️New release of DISGENET plus (v22)
🧬New associations: more than 40K new GDAs and VDAs in the DB
🧪New search functionalities for chemicals in the web and the REST API
⚕️New semantic relations between diseases
👉🏽To learn more about the new features: disgenetplus.com
Due to infrastructure issues at the university, the service is not running since early today, it will be resumed in the next hours. Apologies for any inconvenience.
I am very happy to share our review article “Using Human Genetics to Improve Safety Assessment of Therapeutics”, now published in @NatRevDrugDisc. 🧵
nature.com/articles/s41573-0…
👉🏽 Check our new post on genetic support for FDA drug approvals in 2021
🧬DISGENET plus has genetic support for 90% of FDA drug approvals in 2021
📚This surpasses publicly available resources, which support 66% of drug approvals
#drugefficacy#Geneticsmedbioinformatics.com/geneti…
We are happy to introduce you to our latest feature, the @DisGeNET overlay! Now, you will be able to display directly within PathwayBrowser all the diseases a specific protein has been shown to be associated with!
Frustrated when things don't work together? 🧩😫
#Software, #data & even #datastandards can differ b/w resources, making it hard to streamline #dataanalysis.
'Recommended interoperability resources' are our list of resources overcoming this problem.
bit.ly/2KSjAPg
BridgeDb is a @ELIXIREurope Recommended Interoperability Resources (RIR) and a service of the Interoperability Platform. The purpose of RIRs are to make other tools together easier #ELIXIRRIR
Do you know that @DisGeNET provides different metrics to explore and filter the data? 👉🏽 Check out this interesting meta-analysis on transcriptomic data on Down Syndrome by @maradierssen et al as an example of using our Disease Pleiotropy Index (DPI)