Team

Group leader

Bild: Heddergott

Melanie Schirmer is an Emmy Noether Group leader at the ZIEL – Institute for Food and Health. The research of her lab focuses on computational microbiome research to investigate mechanisms of host-microbial interactions in human diseases. After studying mathematics at the University of Bonn (Germany), she obtained her PhD from the University of Glasgow (Scotland) looking at fine-scale variation in next-generation sequencing data to distinguish natural variation (i.e. single-nucleotide polymorphisms) from errors and biases in the sequencing data. In 2016 she started as a postdoctoral research associate in the Xavier and Huttenhower Groups at the Broad Institute of MIT and Harvard & Harvard T.H. Chan School of Public Health (USA). Her research focused on the human microbiome and the identification of microbial factors involved in the pathogenesis of inflammatory bowel disease and immune responses in healthy individuals. She continued her work at the Broad Institute as a Computational Scientist until she returned to Germany at the start of 2020 to establish her own independent research group.

Postdocs

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Daniela Wetzel is a Postdoctoral researcher in the Schirmer Lab. She studied biology and obtained her PhD in Microbiology at the University of Rostock (Germany) investigating small soluble proteins (SASPs) and germination proteases in spores of Clostridium acetobutylicum. As a PostDoc at the University Medical Center in Göttingen (Germany) in 2016, she gained expertise in the epidemiology of the gastrointestinal pathogen Clostridioides difficile, and as Postdoctoral fellow from 2017 to 2020 she investigated the impact of environmental triggers on C. difficile sporulation and physiology in the McBride Lab at the Emory University School of Medicine in Atlanta (USA). Daniela is interested in the impact of the microbiome on human health and the role of microbial dysbiosis in gastrointestinal diseases. In the Schirmer Lab, her research focuses on the microbiome and potential mechanisms in immune-related diseases.

Bild: S. Sharma

Rajinder Gupta is a postdoc in the Schirmer lab. He started his bachelor in Biotechnology in 2007 at DYPBBI University Pune (India). For his bachelor’s thesis, he worked on the toxicity effects of novel plant extracts. He then joined JUIT (Solan) to pursue a master’s degree in Computational Biology where he explored network motifs in cancer pathways. In 2014, he joined the National Agri-food Biotechnology Institute (Mohali) as a junior research fellow and worked on the development of a universal biomolecular relationship database, extracting and collecting biological interaction data from databases and scientific publications. In May 2016 he joined the department of Toxicogenomics at Maastricht University as a Ph.D. student. He was hired under the EU-ToxRisk project where he was given the opportunity to analyze RNA-Seq data from human cell models through established approaches and to explore new avenues. As part of his postdoctoral work, he is investigating and developing tools and pipelines for microbial metatranscriptomic data.

PhD Students

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Shen Jin is a PhD student in the Schirmer Lab. His research project focuses on understanding the influence of oral microbes on intestinal diseases. Shen obtained his Bachelor's degree in Computer Science at Beihang University, in China. Afterwards, he went to Carnegie Mellon University for his Master's in Computational Biology. Shen is interested in applying computational methods to address biological questions. He has been involved in several research projects, such as developing a deep learning model to identify sequential motifs in DNA and RNA sequences and applying statistical models to understand the sub-cellular organisation of mitochondria.

Research assistant

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Matthias Jung is a bioinformatics student and works as a student research assistant in the Schirmer lab. He holds a diploma in computer science from TU Dortmund and a PhD in mechanical engineering from TUM. His main interest is gaining experience in processing and analysing data from microbiome experiments.