Computational Biology
Introduction
The arrival of next generation sequencing techniques has opened up a wide range of new research areas to study plant microbe interactions. The genomes of phytopathogenic fungi can now be cost-effectively sequenced and gene expression profiles can be determined on a genome-wide scale for both the host plant and the pathogen. Assembly, functional annotation and comparative analysis of the genomes of pathogenic fungi will provide important novel resources to study the fungal side of plant–parasite interactions and to obtain insights into genomic (co-)evolution of interacting organisms.
We focus on applying and developing computational tools to provide these resources. Our research includes collaborations with groups within the Department as well as tight communication with the local central computing facility SUSAN and the Max Planck Genome Centre Cologne (GCC). In addition to our main topics we act as a consultancy for any bioinformatics related question.
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Fungal genomes
Our main interest lies in fungal plant-pathogens with a biotrophic lifestyle: fungi that do not kill the plant but form organs which uptake nutrients from a living plant cell. We study two species with such a lifestyle: the powdery mildews (with Ralph Panstruga) and Colletotrichum higginsianum (with Richard O’Connell). Whole genome sequencing projects have been initiated using 454 (Roche), Solexa (Illumina) and Solid sequencing. The bioinformatics related topics include genome assembly, functional annotation
and comparative analysis. Web-services are implemented to provide public access
to the data.
Regulatory mechanisms
To study regulatory processes during infection genome-wide gene expression profiles are being measured for the host plant and the fungal pathogen. The model plant Arabidopsis thaliana is primarily used to study immune response systems in plants. While on the pathogen side biotrophic fungi are used to study attack mechanisms. Examples of high throughput methodologies used include microarrays, RNA-seq and ChIP-seq. Analyses of these data need solid statistical and computational approaches ranging from study design to machine learning.
Bioinformatics support
Many graduate students and post-docs in the Department perform high throughput experiments yielding large data sets. In order to facilitate the analysis related to bioinformatics ´consultations´ can be requested and short workshops and courses have been developed, a.o. a R/Bioconductor course. Besides, we are heavily involved in the IT infrastructure at the institute.
Interested in joining our group?
We are always interested in highly motivated new colleagues to expand our group and push our research forward. Candidates should be comfortable in working in an interdisciplinary environment as bioinformatics researchers typically come from a variety of backgrounds: Computer science, physics, biology, medicine and mathematics. Students at any level in their career (PhD, MSc, BSc) and with outstanding training in any of these fields are invited to contact us at themaat[a]mpiz-koeln.mpg.de to discuss possible projects.
