There is a fast growing need for well-trained bioinformaticians, specialized in analysing, visualizing and interpreting the massive amounts of data being generated in life science projects.
Therefore, in 2015 and 2013, our committed partners gave ten students (four in 2015, and six in 2013), the exclusive opportunity to be selected for the SIB PhD Fellowship programme. The programme contributes to improving the pool of scientific excellence and to promoting bioinformatics research for life sciences through a 3-year grant. These PhD students are now carrying out their research projects under the supervision of SIB Group Leaders.
Laureates in 2013:
Dennis Haake is working on the development and assessment of an automated ligand design approach (SIB Molecular Modelling Group, supervised by Vincent Zoete and Olivier Michielin, at the University of Lausanne; University of Lausanne fellowship).
Luis Miguel de Oliveira Vilaca is working on the understanding of the mechanisms generating variation and complexity of forms during animal development. His research aims at understanding the development and evolution of skin-appendage patterns (hairs, spines, feathers, scales) and skin colour patterns in vertebrates (SIB Evolutionary Development of Complexity Group, supervised by Michel Milinkovitch, at the University of Geneva; Leenaards Foundation fellowship).
Emma Ricart is working on the combination of bioinformatics tools and MS analyses for high-throughput discovery of new bioactive peptides (SIB Proteome Informatics Group, supervised by Markus Muller and Frédérique Lisacek, at the University of Geneva; University of Geneva fellowship).
Monica Ticlla started her PhD in September 2015 on a cross-talk between infectious diseases, non-communicable diseases and the gut microbiome. (SIB Computational PathoGenOmics Group, supervised by Sebastian Gagneux and Tanja Stadler, at the Swiss TPH Institute and the University of Basel; R.Geigy Foundation fellowship).
Funding partners in 2015:
Laureates in 2013:
Cancer-related aberration events such as genetic aberrations and differentially methylated genes are very different across patients and it is poorly understood how they affect the molecular makeup of the cell, such as the transcriptome and the proteome. In his PhD, Christos Dimitrakopoulos is developing methods that integrate disparate multi-omics data with protein interaction networks in order to explain inter-tumor heterogeneity. His methods elucidate how the different aberration events observed across cancer patients converge functionally to the same signaling pathways (SIB Computational Biology Group, supervised by Niko Beerenwinkel, at the ETHZ; SystemsX.ch fellowship).
Circular RNAs (circRNAs) are a newly discovered class of presumable non-coding RNAs in the mammalian transcriptome. During her PhD, Franziska Gruhl analyzed the genomic properties of circRNAs using RNA-sequencing data from different mammalian species. She has provided first evidence that the formation of many circRNAs is tightly linked to the presence of species-specific and recently active transposable elements (TEs) suggesting an overall neutral and TE-driven model of circRNA formation and evolution (Thesis completed in July 2017 in the SIB Functional Evolutionary Genomics Group, supervisor Henrik Kaessmann, at the University of Lausanne; Leenaards Foundation fellowship).
Malgorzata Nowicka has worked on statistical method development and design of computational pipelines for differential analyses of high-throughput data, including DNA, microarrays, RNA Sequencing and HDCyto data. Two of her main sub-projects were related to DTU analysis based on RNA-seq, which resulted in the DRIMSeq package, and the differential analysis of cytometry data, which resulted in the CyTOF workflow. (Thesis completed in June 2017 in the SIB Statistical Bioinformatics Group, supervised by Mark Robinson, at the University of Zurich; University of Zurich fellowship).
Structural information is key for a detailed understanding of protein function. However, experimental structure determination is an expensive and often laborious process. Computational methods for generating 3D models of proteins are therefore an attractive alternative. In his thesis, Gabriel Studer evaluates state-of-the-art modelling methods, discusses solutions for current shortcomings and provides efficient implementations thereof. The outcome of the thesis has been made available to the scientific community through the SWISS-MODEL web server (Thesis completed in June 2017 in the SIB Computational Structural Biology Group, supervised by Torsten Schwede, at the University of Basel; Swiss Foundation for Excellence and Talent in Biomedical Research fellowship).
Despite its fundamental importance, the question of what terminates growth of organs at their appropriate size is still largely unresolved. In his PhD, Jannik Vollmer has analyzed the growth of the Drosophila eye imaginal disc combining computational modelling and quantitative measurements. He found that the growth rate declines inversely proportional to the area increase and identified the dilution of the cytokine Unpaired as a possible candidate mechanism for growth control (Thesis completed in April 2017 in the SIB Computational Biology CoBi Group, supervised by Dagmar Iber, at the ETHZ; SystemsX.ch fellowship).
Funding partners in 2013: