Who we areAt the Radboudumc Technology Center Bioinformatics we believe that computational biology and big data solutions are key in shaping the data-driven healthcare of the future. We provide complete data analysis solutions, give access to state-of-the-art bioinformatics methods and to the expertise and capabilities of Radboudumc’s bioinformatics community. The RTC is a one-stop-shop for biodata analysis with rapid deployment, with no sacrifices on data safety and privacy, to contribute to Radboudumc’s mission to have a significant impact on healthcare.
- Provide bioinformatics advice, tools, infrastructure and services with clear price structures
- Arrange user groups, courses, network events and expert meetings to bolster interaction
- Enhance research and diagnostics through synergy, specialization and collaborations
- Leverage expertise to create opportunities and funding for clients and consortia’s
- Implement data and software standards for better safety, reproducibility and scaling
Services & expertise
What is bioinformatics?The field of bioinformatics concerns the processing and analyzing of large amounts of biological data using computational methodologies. Bioinformatics combines expertise from many scientific disciplines, like biology, mathematics, statistics, computer science and biochemistry. Bioinformatics analysis can be applied to all sorts of biodata, but the biggest source of data comes from within the cell; genetics and DNA organization, gene expression and protein structures.
How do we apply bioinformatics?Since the completion of the human genome and introduction of high throughput sequencing, the application of bioinformatics has shifted from a purely academic venture towards more clinical use-cases. With the revolution in sequencing, more and more reliable information can be gathered from our cells. Think of investigating disease causing mutations, finding gene expression profiles that lead to cancer metastasis, or analyzing protein structures to identify drug targets.
The RNA-DxP pipelineAt the RTC Bioinformatics, we get the most support requests for RNA Sequencing analysis. In order to both serve our clients and to contribute to a data-driven heathcare, we created the RNA-DxP pipeline. With this pipeline we aim to create a RNA-Seq data analysis workflow which is robust, reproducible and scalable, while still being innovative and feature complete. RNA-DxP is suitable for both biological as biomedical research, human and model organisms. We are working together with the Radboudumc department of Genetics to make RNA-DxP available for patient diagnostics purposes. The current features are:
- Advanced QC and Metrics
- Differential Gene Expression
- Alternative and Differential Splicing
- Fusion Gene detection
- Splice Junction analysis
- Pathway & GO Enrichment
- EnrichR and String Annotation
- RNA Variant Calling and Annotation
- Automated reporting and visualizations
- Scaled for projects of any size
Our analysis services and solutions
- Thorough and interactive visualized QC analysis
- Differential Gene Expression Analysis
- Pathway analysis and Annotation
- Single Cell data analysis
- Transcriptome analysis
- Isoform detection and Rare disease diagnostics
- Publication-grade graphics and plots
- Single Nucleotide and Structural Variant calling and annotation
- Sequence analysis and pattern recognition
- Genome assembly, annotation and visualization
- Comparative Genomics and Phylogenetics
- Bacterial classification and Pathogen marker analysis
- Somatic/Tumor variant calling
Protein Structure analysis
- Protein homology modeling and function prediction
- 3D-analysis of mutational effects
- Analysis of structures and complexes based on 3D projections
- 16S and Marker Gene classification
- Microbiome Functional annotation
- Metagenome assembly
- Comparative Microbiomics analysis
- Ontology and Text mining
- Integration with biostatistics
- Investigating use of Machine/Deep learning
- Big data visualizations
- Data management
- Data analysis automation and upscaling
Future DevelopmentsTo facilitate the data-intensive future of medicine, bioinformatics technologies can be a driver for new hypotheses and solutions.
- By leveraging combined infrastructure and expertise, standardized data analysis workflows will be setup that can deal with both singular research questions and large-scale projects.
- Pooled recourses and scaling up computational infrastructures will result in shorter turnover times and faster answers.
- Hybrid revenue models and external or commercial projects will help with creating a workforce that can deal with big biodata for all stakeholders.
- Integrating bioinformatics pipelines with available R&D infrastructure will create a one-stop-shop for biodata analysis with rapid deployment, yet with no sacrifices on data safety and privacy.
- Software development and data management practices will be upgraded to industry standards, which will provide better reproducibility and efficiency.
HOPE User-friendly web serviceHOPE analyzes the structural effects of a point mutation in a protein sequence. Input your protein sequence and the mutation and HOPE will collect and combine available information from a series of web services and databases and will produce a report, complete with results, figures and animations. go to HOPE
News & agenda
LUMO Labs and Oost NL invest in AiosynInvestment accelerates development of artificial intelligence platform to improve diagnostics7 February 2022
DeepRank: a deep learning frameworkfor data mining 3D protein-protein interfaces8 December 2021
Dutch-Nordic Alliance for Precision Cancer Medicine launched26 November 2021