DrugComb retweeted
How to improve the reproducibility of drug sensitivity screens? Make your data FAIR! Check our community-driven efforts here: academic.oup.com/bib/advance…
@EatrisEric @FIMM_UH @ncats_nih_gov @UCPH_BRIC @WennerbergLab @EoscLife @IMTM_Olomouc @EuOpenscreen @MarioNegriIRCCS
DrugComb retweeted
Can deep-learning improve the encoding of molecular structure of a drug to understand their interactions? Check on our comparative study! Congratulations on @b_zagidullin @epitkane @gyuanfan
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DrugComb retweeted
Great resources for drug sensitivity data!
DrugComb update is out! Check more details at academic.oup.com/nar/advance…
DrugComb update is out! Check more details at academic.oup.com/nar/advance…
DrugComb retweeted
I am speaking at MCBIOS and MAQC Joint 2021 Virtual Conference. Please checkout the details of my talk at: whova.com/xems/apis/opengrap…
DrugComb retweeted
DrugComb update paper is out! Much more drug sensitivity data resources and web applications are made available!
biorxiv.org/cgi/content/shor…
DrugComb retweeted
Congrats to the team! This was fun and educational.
Thrilled to be a winner of the antiPD1 response prediction @DR_E_A_M challenge! synapse.org/#!Synapse:syn184…
Great to have @emmyverschuren and your group on board! @HelsinkiUniMed @FIMM_UH @helsinkiuni @iCAN_Finland
DrugComb retweeted
I am happy to be the guest editor for the special issue of 'Network Pharmacology Modelling for Drug Discovery' in the journal of Processes. Hope to receive more insights from you! mdpi.com/si/71499
DrugComb retweeted
SynergyFinder is updated! Please go to synergyfinder.org to find more! @DrugComb @NetPharMed @DrugTargetCommons
DrugComb retweeted
Enlightening cancer drug discovery with challenge-winning AI solutions | University of Helsinki helsinki.fi/en/news/health-n… @DR_E_A_M @iCAN_Finland @FIMM_UH
DrugComb retweeted
Very happy that our work on the modeling of the concepts in traditional medicine with multipartite networks is out (frontiersin.org/article/10.3… ) @NetPharMed @DrugComb
@FrontiersIn @FrontPharmacol
We are looking for a talented post-doc to leverage the huge amount of drug combination/drug target interaction data to model the drug-target-disease networks! Apply by 30.9 via bit.ly/3j2eKvM
DrugComb retweeted
Very happy that our work on the ratio of coherency between the expression level and the causal relationships among the gene pairs is out(mdpi.com/2218-273X/10/6/850)#mdpibiomolecules
"Can We Assume the Gene Expression Profile as a Proxy for Signaling Network Activity?" @Biomol_MDPI
DrugComb retweeted
RNA Atlas of Human Bacterial Pathogens Uncovers Stress Dynamics Linked to Infection biorxiv.org/cgi/content/shor… #biorxiv_micrbio
Packages used by DrugComb analysis service are updated under R (3.6.0) to:
- TidyComb github.com/DrugComb/TidyComb (version 0.0.5)
- SynergyFinder bioconductor.org/packages/re… (version 2.0.3)
New single drug screen data from beatAML is uploaded to DrugComb.
There are 528 cell lines (new primary cultured AML cells), 123 molecules (4 new molecule),
and 47650 single drug dose response blocks.
DrugComb API is available right now. More details can be found in the following link:
drugcomb.fimm.fi/api/
Single drug data is added to DrugComb comes from PharmacoDB dataset v1.1.1. It contains single drug dose-response experiments from 7 original datasets: UHNBreast, gCSI, CCLE, FIMM, GRAY, GDSC1000, CTRPv2. There are totally 650894 single drug-cell experiments.












