scTherapy, a novel machine learning approach from Tero Aittokallio and colleagues, leverages single-cell transcriptomic profiles to identify multi-targeting treatment options for individual patients with hematological cancers or solid tumors. https://t.co/pnfca8Bt3c
Researchers at FIMM have developed an effective computational platform that automatically identifies cell types from #SpatialTranscriptomics data. The method holds great potential for understanding tissue organisation in both health and disease.
💻⬇️
https://t.co/lQIGbNbF1v
Want to find out more about #REMEDi4ALL researchers?🔬
Read about PhD student Kristen Nader's (@FIMM_UH) #DrugRepurposing research, career goals and chosen superpower in the latest edition of Early Career Researcher Insights⬇️
[https://t.co/gWuZ2Q4hfC]
scType
Marker-based cell type annotation for #SpatialTranscriptomics Visium Slide-seq
Use positive + negative markers (from scTypeDB database with previously scRNAseq-identified cell type markers or custom marker genes), instead of deconvolution.
R & Python
https://t.co/Xnbou90pJp or https://t.co/Qhwwa3AibV
Mitro Miihkinen lab Bioinformatics 2024 @mitroe
https://t.co/VuJNElz0nf
Danielle Nader, RCSI PhD student, has been awarded the Royal Academy of Medicine Ireland Donegan Medal.
#COVID19research@RCSI_Research@RAMIreland
https://t.co/yzMnhgGgaS