Ulas Lab

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Ulas Lab

Ulas Lab

@Ulas_Lab

Happpy father and husband. Head of Bioinformatics PRECISE at University of Bonn and at Deutsches Zentrum für Neurodegenerative Erkrankungen e.V. Bonn, Germany.

Katılım Mart 2018
232 Takip Edilen133 Takipçiler
Ulas Lab
Ulas Lab@Ulas_Lab·
🧬 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 @ImmunoTal+@Ulas_Lab #Bioinformatics @UniBonn @ImmunoSens 🧫🔬🧪
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Biology MDPI
Biology MDPI@Biology_MDPI·
Co-expression networks have been utilized as a method to describe and study gene relationships. Furthermore, it can be utilized to integrate different omics datasets. 🎈Find more at mdpi.com/si/119775 Welcome to share your latest research results with us! #CallForPapers
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Ulas Lab
Ulas Lab@Ulas_Lab·
🧬 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
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Ulas Lab
Ulas Lab@Ulas_Lab·
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! @LorenzoBonaguro @jsschrepping
Schultze Lab@LabSchultze

Are you an immunologist & want to dive into the omics world? Then this might be a good start! Super excited to share our guide to systems-level immunomics, online now in @NatImmunol go.nature.com/3dFFMeY Congratulations to our very own @LorenzoBonaguro @jsschrepping @urealtomek

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Ulas Lab
Ulas Lab@Ulas_Lab·
We showcase #hCoCena by integrating two public datasets that describe a similar experimental setup but were generated using different technologies, identifying co-expression motifs shared by the two datasets and those unique to one another.
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Ulas Lab
Ulas Lab@Ulas_Lab·
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.
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