We have open positions for Phd students and Postdocs (m/f/d) in our lab.
If you would love to work on super exciting projects in the single cell sequencing field (with a special focus on metabolic RNA labeling), have a keen interest in data analysis method development and a degree in statistics, computer science, bioinformatics or biology (with a strong bioinformatics background), please send a letter of motivation and your CV to jobs [at] erhard-lab [dot] de!
Stefan joined our team in Regensburg. We wish him a lot of success and fun!
Our preprint on rescuing previously unmappable reads as well as correcting reverse transcrition mediated bias in quantification of nucleotide conversion RNA-seq data is on bioRxiv. Thanks Kevin for a major effort!
We welcome Michael Lappe in our lab and wish him all the best for his research!
Our lab moved from the Institute for Virology and Immunobiology at the University of Würzburg at the new Faculty for Informatics and Data Science at the University of Regensburg. We are absolutely excited and look forward to all future challenges.
Collaboration with Cochain-lab: Integrated single-cell analysis-based classification of vascular mononuclear phagocytes in mouse and human atherosclerosis
Collaboration with Schlosser lab: Extending the Mass Spectrometry-Detectable Landscape of MHC Peptides by Use of Restricted Access Material
Collaboration with Fischer lab: An unusual mode of baseline translation adjusts cellular protein synthesis capacity to metabolic needs
Collaboration with Dölken lab: Two murine cytomegalovirus microRNAs target the major viral immediate early 3 gene
Collaboration with Dölken lab: pUL36 Deubiquitinase Activity Augments Both the Initiation and the Progression of Lytic Herpes Simplex Virus Infection in IFN-Primed Cells
The combination of single-cell RNA sequencing (scRNA-seq) with metabolic RNA labelling approaches now enables time-resolved monitoring of transcriptional responses for thousands of genes in thousands of individual cells in parallel.
A preprint on our grandR package is now on bioRxiv. It offers easy access to all different kind of downstream analysis for nucleotide conversion RNA-seq data (such as SLAM-seq or TUC-seq), and introduced new computational methodology for quality control and temporal recalibration as well as a Bayesian hierarchical model to analyze synthesis and degradation rates from single snapshot experiments as well as changes thereof. Thanks Teresa and Lygeri for a major effort!
Kilian joined our group. We wish him a warm welcome a lot of success and fun!
Congratulations to Chris for a great defense of his PhD! We wish you all the best!