At March 15, I started as a data steward at the Center for Molecular Medicine (CMM) at the UMC Utrecht in the research group led by Jeroen de Ridder.
Being a data steward, I promote - and advice on how - to practice Open Science, within the privacy regulations and according to the FAIR principles.
In addition, I am one of the members of the DAC (Data Access Committee) for the EGA (European Genome-Phenome Archive), led by Ies Nijman of the UBEC (UMCU Bioinformatics Expertise Core). Especially, I want to contribute to user-friendly, easily comprehensible, straightforward and useful guidelines and/or templates to ensure the different types of omics data will be FAIR “for each other”.
I am very pleased to be part of the X-omics project and look forward to work with you all to achieve great results!
After months of study at home (due to Covid-19) and a long summer break I was very happy to start working at the Centre for Molecular and Biomolecular Informatics (CMBI) in Nijmegen as Scientific Programmer. My activities here are part of the X-omics initiative.
I followed the master program Molecular Genetics & Biotechnology at the Leiden University. During this master I developed an interest for computational biology and therefore I chose to do research internships that gave me the opportunity to get hands-on experience with bioinformatics. My first internship was at the Institute of Biology Leiden (IBL), where I combined both wet- and dry lab research to study a Biosynthetic Gene Cluster in Streptomyces, under supervision of Gilles van Wezel. My second internship was at the Neurogenetics group of the UMC Utrecht, under supervision of Jan Veldink. Here, I studied (expanded) short tandem repeats that can cause ALS. Specifically, I developed a tool to study the presence of interrupting DNA motifs in these repetitive DNA elements.
For X-omics, I am currently involved in the ACTION demonstrator project and in close collaboration with Anna Niehues I am also working on the Digital Research Environment (DRE). All in all, I am very pleased to be part of X-omics, where I think I can both prove and develop my skills/knowledge in the different -omics types or research.
I’m a PhD student at the University of Groningen (UG), where I work at the European Research Institute for the Biology of Ageing (ERIBA) and at Groningen Research Institute of Pharmacy (GRIP), my 2 promoters are Peter Horvatovich, from the department of Analytical Biochemistry at the UG and Victor Guryev from the Group of Genome Structure and Ageing (University Medical Center Groningen, UMCG) are both part of X-omics Netherlands Infrastructure Consortium as well. Currently, I am involved in the X-omics project with the goal of making a ‘portable’ pipeline to perform proteogenomics analysis from start to end.
I previously studied Bioinformatics at the Hogeschool van Arnhem & Nijmegen. During my Bsc I did an internship at the bacterial genomics group at the Center for Molecular and Biomolecular Informatics (CMBI). Following this research experience, I did another at the Hubrecht institute in Utrecht where Victor Guryev was my supervisor. After I graduated I went to Wageningen University & Research centre (WUR). Here, I did my master theses at the departments of Animal Breeding and Genetics (ABG) and Systems & Synthetic Biology (SSB). After finishing I applied for a job at the department of Experimental Cardiology at the UMCG. During my research there, I was working as a data-analyst/bioinformatician focused on performing GWAS analysis in the context of medical/cardiac phenotypes.
I regretted focusing solely on genomics and transcriptomics and not learning more about proteomics and other omics layers. This PhD within the X-omics Consortium allows me to work at the crossroads of sequencing and mass spectrometry data as part of the data integration and stewardship pillar. I’m interested in bringing the complexities of genomics and transcriptomics to the proteomics field. The integration of the patient specific protein variants to create personalized protein sequence databases, which can be used for database searching large LC-MS/MS datasets and to identify patient specific variants that have implications in complex diseases such as cancer and COPD. Currently, proteomics analysis pipelines rely on canonical sequences from (curated) public databases such as Ensembl and Uniprot. Simply including all possible ‘translate-able’ sequences leads to a large search space and low statistical power to identify protein variants. The goal of my PhD project is to provide a proteogenomics pipeline, which uses genomics and/or transcriptomics data to make a protein database containing all protein variants present in a clinical/biological proteomics sample that is both small and accurate without including large amounts of hypothetical proteins for which there is no support in the genomics or transcriptomics data. In case you have similar interests - let’s collaborate!
Anna Niehues is a postdoc at Radboudumc, Nijmegen, where she works at the Center for Molecular and Biomolecular Informatics (CMBI), led by Peter-Bram ’t Hoen, and the Translational Metabolic Laboratory, led by Alain van Gool. She is currently involved in the X-omics project and the European EATRIS-Plus project. Anna previously studied Biosciences at the University of Münster (WWU) in Germany, where she also obtained her PhD. She has been working as a bioinformatician on mass spectrometry data analysis in the context of quantitative proteomics, and structural analysis of carbohydrate oligo- and polymers.
Within the X-omics project, she works as data scientist in the data analysis, integration and stewardship pillar, together with Peter-Bram ’t Hoen (work package leader) and Gurnoor Singh (data steward) from Radboudumc and other X-omics collaborators across the Netherlands. She is interested in the integration of mass spectrometry-derived data such as metabolomics data with other types of omics data in order to e.g. increase the power of biomarker studies or gain additional insights into the relationships between different molecular levels and their association with disease phenotypes. She is also interested in FAIR data analysis workflows which, alongside FAIR data, provide the means for reproducibility of multi-omics data analyses.