Project (Tim Beißbarth & Michael Altenbuchinger)

At the department of Medical Bioinformatics of the University Medical Center Göttingen we have an opening for one PhD student position.

The research focus of our department is on methods to evaluate biomedical data and applications in Systems Medicine. We develop methods to statistically or bioinformatically analyze and understand especially high-dimensional data sets coming from biomedical research (e.g. genome sequencing, transcriptomics and proteomics) and to apply these methods in biomedical research.

Especially, genomics, transcriptomics, proteomics and other omics as well as the integrative analysis and meaningful interpretation of such different data types pose major challenges for method development, where the methods have to be tailored towards the specific applications. We therefore apply methods from the area of machine learning or artificial learning as well as statistical computing.

We are looking for ambitious PhD candidates who want to be at the forefront of research in medical bioinformatics. Our new projects are rooted in themes focusing on the Long/Post-COVID syndrome and the improvement of treatment outcomes, which involves the use of innovative artificial intelligence (AI) and multidisciplinary expertise to analyze molecular and clinical data from LC/PC patients.
Another key area of focus is the prediction of treatment outcomes in pancreatic cancer, where we integrate multi-omics data and histopathology images into a multimodal learning approach.

• Chereda H, Leha A, Beißbarth T. Stable feature selection utilizing Graph Convolutional Neural Network and Layer-wise Relevance Propagation for biomarker discovery in breast cancer. Artif Intell Med. 2024 May;151:102840. doi: 10.1016/j.artmed.2024.102840. Epub 2024 Mar 11. PMID: 38658129.
  
  
• CODEX: COunterfactual Deep learning for the in silico EXploration of cancer cell line perturbations. Schrod S, Zacharias HU, Beißbarth T, Hauschild AC, Altenbuchinger M.Bioinformatics. 2024 Jun 28;40(Suppl 1):i91-i99.
  
  
• Schrod S, Lück N, Lohmayer R, Solbrig S, Völkl D, Wipfler T, Shutta KH, Ben Guebila M, Schäfer A, Beißbarth T, Zacharias HU, Oefner PJ, Quackenbush J, Altenbuchinger: Spatial Cellular Networks from omics data with SpaCeNet. M.Genome Res. 2024 Oct 11;34(9):1371-1383.
  
  
• Sahrhage M, Paul NB, Beißbarth T, Haubrock M. The importance of DNA sequence for nucleosome positioning in transcriptional regulation Life Sci Alliance. 2024 Jun 3;7(8):e202302380.