🧬 Are you a bioinformatics wizard looking for a challenge? The University of Bonn invites you to join our team! Explore immunological bulk and single-cell transcriptome data in a cutting-edge research environment. Apply now for a Dec 2023 start!🌟 #PhDPosition #Bioinformatics
#cherryblossom walk at the #rheinaue in #Bonn #Germany with my favorite #bioinformaticians Ulas Lab and Amir Hossein Kayvanjoo #helloSpring #Collaboration #Bioinformatics
After a long journey, I am happy to share that our paper on the dysregulation of blood neutrophils in #COPD is finally out Cell Reports. A huge collaborative work between Schultze Lab, Hansbro Research Fabian Theis Martijn Nawijn Herbert B Schiller A. Önder Yildirim Jan Hasenauer Ulas Lab and
Very proud of this piece that summarizes what we have learned (sometimes painfully) over the past years using #omics techniques for #immunology . For sure #teamwork is the most important factor! Lorenzo Bonaguro Jonas Schulte-Schrepping
We are excited to announce that our tool #cocena has been published #openaccess in OUP Bioinformatics by @MarieO126 and the team!! It offers advanced #CoexpressionNetwork analysis including #dataintegration . Check it out here👉bit.ly/3DfSwDc. kongu Schultze Lab @limes @dzne
🧬 Bioinformatics PhD 📢🚨! Be part of our MSCA Doctoral Networks at the University of Bonn. Explore bulk and single-cell immunological data in advanced research. Exciting opportunity awaits! Apply now! Dreamteam Tal Pecht (Ph.D.) 💔+Ulas Lab #Bioinformatics Rheinische Friedrich-Wilhelms-Universität Bonn ImmunoSensation 🧫🔬🧪
Very proud of Lisa Holsten who presented her work on our collaboration with AG Viemann Universitätsklinikum Würzburg deciphering the neonatal #immunesystem during #Influenza infection using #hcocena
🎉Congratulations to our members Joachim L. Schultze Schultze Lab Jan Hasenauer Melania Capasso DZNE Research Center Ulas Lab and colleagues!
The #Coxpression analysis can be further expanded by a large variety of analyses, allowing in-depth data exploration, including hub detection, #PCA , count distributions, metadata correlation, geneset visualization, network models, #TranscriptionFactor prediction, and more.