Network Pharmacology for Precision Medicine Research Group @helsinkiuni @amchelsinki
Helsinki, Finland
Joined June 2018
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TangLab retweeted
👏 Presenting the amazing team behind the project!
Meet our consortium of partners spanning 23 organizations from 14 different countries🌏 A huge thanks to all joining us onsite and virtually! We are grateful for the energy, ideas, and enthusiasm that everyone brought today.
Great to be part of the consortium to develop digital twin models for cancer drug discovery! #digitaltwins
Congratulations on defending your dissertation on the multi-omics analysis of drug resistance in #MultipleMyeloma, Alina! A firm testimony of endurance through hardship. Big thanks to the opponent Dr. @CascioneLuciano for making it happen! @ISBSIB @FIMM_UH @OrionPharma #oncosys
It's great to know that our group has been granted funding from @Syopajarjestot @Syopasaatio! Thank you for entrusting us with our projects on combating drug resistance in cancer.
And congrats to #oncosys researchers @annimariav and @NetPharMed for research grants! As well as #oncosys young researchers @ntn_mai, Jun Dai and Sanna Pikkusaari for PhD grants.
Consider to submit your next bioinformatics paper to GPB@GPBees!
Exciting news! 🎉 Our journal "Genomics, Proteomics & Bioinformatics" (GPB) has achieved an impressive 2-year Impact Factor of 11.5 and a 5-year Impact Factor of 10.3! 🧬🧪 #Genomics #Proteomics #Bioinformatics #ImpactFactor Follow us on Twitter: @GPBees
Warmest congratulations to @JehadAldahdooh on the successful PhD defense! Your hard work and persistence have paid off well. It has been a great honor to be the supervisor! Wish you all the success ahead!
I successfully defended my PhD on Friday! Immense gratitude to Prof. Hong-Gee Kim for the insightful feedback and to Dr. Jing Tang and Dr. Ziaurrehman Tanoli for their unwavering support. Thank you to everyone who cheered me on throughout this journey @NetPharMed @UnivHelsinkiCS
We are organizing the edition of 'Methodological developments in systems biology'. Your articles on the modeling of treatment responses and clinical outcomes are particularly welcomed! @Nature_NPJ
nature.com/collections/chdbd…
Finally out! We proposed a top-performing model to predict the survival of lung cancer patients for the Anti-PD1 treatment. @DR_E_A_M @bmsnews #Immunotherapy
rdcu.be/dzpdZ
Check the details of the model here: synapse.org/#!Synapse:syn242…
Let us rebuild hope through our small actions, even though it seems faint. Blessed are those who can give!
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TangLab retweeted
Press release of our recent @NatureComms published study:
Sister cells uncover pre-existing resistant states in cancer helsinki.fi/en/news/cancer/s…
Thrilled to co-announce our paper's acceptance in Nature Communications! 4-years of persistence in collaboration pays off finally😇. Stay tuned for more discoveries in cancer treatment!👍
How do #cancer cells with resistant fates differ from the sensitive, already before the treatment? To answer this, we developed ReSisTrace, a cellular time-travel method that uses the similarity of sister cells to trace back pre-existing resistance. nature.com/articles/s41467-0…
Nice to be part of the great consortium to implement FAIR principles for life sciences data! We are committed to the FAIR principles in our method development. @DrugComb @SynergyFinder micha-protocol.org
Celebrating the creation of #DataSpace for the #LifeSciences at the 4th & final EOSC-Life AGM (#eosclifeAGM23) in Brussels!
🥳
Partners shared tools, resources, & services, plus how these are being carried over into new projects like:
➡️@BYCOVID_eu
➡️@EOSC4Cancer
➡️@GDI_EUproject
ALT A large group of people stands in a room in front of a screen. The screen displays the EOSC-Life logo.
Generosity is a profound blessing that requires the courage/faith to act upon it. - summarized by ChatGPT😅
Congratulations on the success of the Compound Solubility Prediction Challenge! We would like to thank Wenyu, our exceptional PhD student, for his invaluable contributions to the organizing team!
Happy to learn that our paper has been selected for the PLOS Showcase collection! Understand the meridian theory in traditional Chinese Medicine by AI growkudos.com/publications/1… via @growkudos
Happy to introduce a new R package for dose-response curve fitting! With drda, it is possible to fit models by the method of least squares, perform goodness of fit tests, and conduct model selection. User feedback is appreciated! doi.org/10.18637/jss.v106.i0…
Well done @b_zagidullin for the interpretable prognostic modeling of endometrial cancer! Nice collaboration within the #oncosys program.
we published a paper! nature.com/articles/s41598-0…
1/n if you wanna do survival analysis, make sure to assess both model discrimination and calibration, using eg C-index and Brier score. Especially if you are using fancier ML methods
Finally out! We provided a decision tree model to stratify lung cancer patients for immunotherapy. The model won the @DR_E_A_M challenge, and more importantly, it can be directly implemented in the clinics to help patients. #cancer #immunotherapy biorxiv.org/content/10.1101/…
ALT This is how the prediction works: For non-small cell lung cancer patients, the immunotherapy treatment response is an interaction between two clinical biomarkers, TMB (Tumor mutation burden) and PDL1 expression. If a patient's TMB is lower than 242 (i.e. the total number of mutations is less than 242), then the patient is not responding to the antiPD1 treatment; however, if a patient's TMB is higher than 242, then the antiPD1 treatment response is related to the PDL1 expression level (i.e. higher PDL1 expression suggests a better response to the antiPD1 treatment).
If a patient's TMB is lower than 242 (i.e. the total number of mutations is less than 242), then the patient is not responding to the antiPD1 treatment;