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Radboud Technology Center Bioinformatics, Radboudumc

Contact Details

Radboudumc

Radboud Technology Center Bioinformatics, Radboud University Nijmegen Medical Centre PO Box 9101 6500 HB Nijmegen

https://www.radboudumc.nl/rtcbioinformatics

Sander Bervoets

sander.bervoets@radboudumc.nl

0031 (0)24 3619390

Hotel Description

The Radboudumc Technology Center (RTC) Bioinformatics was founded to organize bioinformatics as a technological resource, for both the Radboudumc and beyond. The RTC is part of the Center for Molecular and Biomolecular Informatics (CMBI) department within the Radboud Institute for Molecular Life Sciences (RIMLS) institute in Nijmegen.

We provide complete data analysis solutions, give access to state-of-the-art bioinformatics methods and leverage the expertise and capabilities of the bioinformatics and computational biology community available within the Radboud campus. By combining shared infrastructure and standardized data analysis workflows, the RTC is a one-stop-shop for biodata analysis with rapid deployment. Software development and data management practices are up to industry standards, which will provide better reproducibility, scaling and efficiency with no sacrifices on data safety and privacy.

By enabling scientists to better utilize the big data generated within biomedical research, the CMBI and the RTC Bioinformatics will contribute to making healthcare innovative, cost-effective and personalized.

 

Bioinformatics
Public
  • Biodiversity & ecology
  • Biomedical & health
  • Agri & Food
  • Industrial biotech
  • Genomics
  • Next generation sequencing
  • Protein Modelling
  • Text Mining
  • Molecular Diagnostics
  • Metabolic flux modelling
  • Microbiome
  • Protein structure
  • Molecular genotype-phenotype classification

Expertise and Track Record

43500985056 Unraveling the secrets of autoreactive B cells in Sjögren’s syndrome patients with R. Thurlings (Radboudumc). 435000002 Microbiome and Skin Diseases with Dr P.M.J.L. Zeeuwen (UMC Radboud). 435000031 Skin Micobiome Dynamics in Canine Atopic Dermatitis with prof. dr. V.P.M.G. Rutten (UU)

The Unique selling point of the RTC Bioinformatics is the ability to combine academic research capabilities with commercial-grade support and service. By leveraging the expertice from the Radboud UMC and Radboud University we can provide value adding insights to most biological, medical or scientific questions. We also have access to comprehensive computational clusters and sequencing facilities.

We are about to release a industry-grade RNA-Seq analysis pipeline which will tackle both biological and diagnostical datasets. Combined with advanced data QC, interactive visualisations, and extended biological intrepetation this tool will be a one-stop pipeline for many data analyses. In the near term, it will also encompass Single Cell RNA-Seq.

We developed a tool to analyze epigenetics data to be able to align and cluster them. In applying this tool we have collaborated in the analysis of epigenetics data for Myeloid Leukemia:
Chromatin accessibility, p300, and histone acetylation define PML-RARα and AML1-ETO binding sites in acute myeloid leukemia. Saeed S, Logie C, Francoijs KJ, Frigè G, Romanenghi M, Nielsen FG, Raats L, Shahhoseini M, Huynen M, Altucci L, Minucci S, Martens JH, Stunnenberg HG. Blood. 2012 Oct 11;120(15):3058-68.

We collaborate in applying our extensive knowledge of protein structures and the massive selection of tools designed for their implementation to explain the molecular causes of an important disease:
Dominant missense mutations in ABCC9 cause Cantú syndrome. Harakalova M, van Harssel JJ, Terhal PA, van Lieshout S, Duran K, Renkens I, Amor DJ, Wilson LC, Kirk EP, Turner CL, Shears D, Garcia-Minaur S, Lees MM, Ross A, Venselaar H, Vriend G, Takanari H, Rook MB, van der Heyden MA, Asselbergs FW, Breur HM, Swinkels ME, Scurr IJ, Smithson SF, Knoers NV, van der Smagt JJ, Nijman IJ, Kloosterman WP, van Haelst MM, van Haaften G, Cuppen E. Nat Genet. 2012 May 18;44(7):793-6. doi: 10.1038/ng.2324.

We host researchers, in this case an RIVM PhD student, to help en guide NGS data analysis and interpretation in this case in a collaboration with the RIVM and the Sanger Centre (UK).
Inferring patient to patient transmission of Mycobacterium tuberculosis from whole genome sequencing data. Bryant JM, Schürch AC, van Deutekom H, Harris SR, de Beer JL, de Jager V, Kremer K, van Hijum SA, Siezen RJ, Borgdorff M, Bentley SD, Parkhill J, van Soolingen D. BMC Infect Dis. 2013 Feb

We are collaborating with the X-omics Initiative through the close cooperation with the CMBI. Within this initiative, many types of omics datasets are combined to increase our insight for the complex data-driven biomedical research of tomorrow.

  • 3D-e-Chem-VM: Structural Cheminformatics Research Infrastructure in a Freely Available Virtual MachineMcGuire R, Verhoeven S, Vass M, Vriend G, de Esch IJP, Lusher SJ, Leurs R, Ridder L, Kooistra AJ, Rischel T, de Graaf C 2017; J Chem Inf Model, Feb 14. doi: 10.1021/acs.jcim.6b00686. [Epub ahead of print] Details A team of cheminformatics and bioinformatics researchers from Centre for Molecular and Biomolecular Informatics, Netherlands eScience Center, BioAxis Research, and Vrije Universiteit Amsterdam have developed a freely available virtual machine to enable computer-aided drug design.
  • Tools and data services registry: a community effort to document bioinformatics resources. Ison J, Rapacki K, Menager H, Kalas M, Rydza E, Chmura P, Anthon C, Beard N, Berka K, Bolser D, Booth T, Bretaudeau A, Brezovsky J, Casadio R, Cesareni G, Coppens F, Cornell M, Cuccuru G, Davidsen K, Vedova GD, Dogan T, Doppelt-Azeroual O, Emery L, Gasteiger E, Gatter T, Goldberg T, Grosjean M, Gruning B, Helmer-Citterich M, Ienasescu H, Ioannidis V, Jespersen MC, Jimenez R, Juty N, Juvan P, Koch M, Laibe C, Li JW, Licata L, Mareuil F, Micetic I, Friborg RM, Moretti S, Morris C, Moller S, Nenadic A, Peterson H, Profiti G, Rice P, Romano P, Roncaglia P, Saidi R, Schafferhans A, Schwammle V, Smith C, Sperotto MM, Stockinger H, Varekova RS, Tosatto SC, de la Torre V, Uva P, Via A, Yachdav G, Zambelli F, Vriend G, Rost B, Parkinson H, Longreen P, Brunak S. Nucleic Acids Res, 2016 Jan 4;44(D1):D38-47
  • GPCRdb: the G protein-coupled receptor database - an introduction Munk C, Isberg V, Mordalski S, Harpsoe K, Rataj K, Hauser AS, Kolb P, Bojarski AJ, Vriend G, Gloriam DE. Br J Pharmacol., 2016 Jul;173(14):2195-207
  • KMAD: knowledge-based multiple sequence alignment for intrinsically disordered proteins. Lange J, Wyrwicz LS, Vriend G. Bioinformatics, 2016 Mar 15;32(6):932-6
  • New Biological Insights from Better Structure Models. Touw WG, Joosten RP, Vriend G J Mol Biol., 2016 Mar 27;428(6):1375-93
  • A series of PDB-related databanks for everyday needs. Touw WG, Baakman C, Black J, Te Beek TA, Krieger TA, Joosten RP, Vriend G.Nucleic Acids Res., 2015 Jan 28;43(Database issue):D364-8. doi: 10.1093/nar/gku1028
  • Key challenges for the creation and maintenance of specialist protein resources. Holliday GL, Bairoch A, Bagos PG, Chatonnet A, Craik DJ, Finn RD, Henrissat B, Landsman D, Maning G, Nagano N, O'Donovan C, Pruitt KD, Rawlings ND, Saier M, Sowdhamini R, Spedding M, Srinivasan N, Vriend G, Babbit PC, Bateman A. Proteins, 2015 Jun;83(6):1005-13. doi: 10.1002/prot.24803
  • Inferring metabolic states in uncharacterized environments using gene-expression measurements. Rossell S, Huynen MA, Notebaart RA. PLoS Comput Biol. 2013 Mar;9(3) A new method to predict metabolic fluxes using gene expression data reliably predicts genes essential for growth, and can be used to prioritize drug targets Microbiome dynamics of human epidermis following skin barrier disruption. Zeeuwen PL, Boekhorst J, van den Bogaard EH, de Koning HD, van de Kerkhof PM, Saulnier DM, van Swam II, van Hijum SA, Kleerebezem M, Schalkwijk J, Timmerman HM. Genome Biol. 2012 Nov 15;13(11):R101. Providing data analysis tools for 16S population profiling analysis and new interpretation methods in collaboration with NIZO food research and the dermatology department (RUMC).
  • Iterative orthology prediction uncovers new mitochondrial proteins and identifies C12orf62 as the human ortholog of COX14, a protein involved in the assembly of cytochrome c oxidase. Szklarczyk R, Wanschers BF, Cuypers TD, Esseling JJ, Riemersma M, van den Brand MA, Gloerich J, Lasonder E, van den Heuvel LP, Nijtmans LG, Huynen MA. Genome Biol. 2012 Feb 22;13(2):R12. A new, sensitive and reliable method to predict orthologous relationships between proteins uncovers new proteins involved in oxidative phosphorylation that we have shown to be mutated in patients with mitochondrial disease.
  • Protein structure analysis of mutations causing inheritable diseases. An e-Science approach with life scientist friendly interfaces. Venselaar H, Te Beek TA, Kuipers RK, Hekkelman ML, Vriend G. BMC Bioinformatics. 2010 Nov 8;11:548. Automated, reliable prediction of the effect of mutations on protein 3D structure and function. A series of PDB related databases for everyday needs. Joosten RP, te Beek TA, Krieger E, Hekkelman ML, Hooft RW, Schneider R, Sander C, Vriend G. Nucleic Acids Res. 2011 Jan;39(Database issue):D411-9. Demonstrates our experience in making databases interoperabel Bayjanov JR, Molenaar D, Tzeneva V, Siezen RJ, van Hijum SA. PhenoLink—a web-tool for linking phenotype to ~omics data for bacteria: application to gene-trait matching for Lactobacillus plantarum strains. BMC Genomics. 2012 May 4;13:170. A widely used software web-tool for phenotype to omics correlation. http://bamics2.cmbi.ru.nl/websoftware/phenolink

The NewProt EU project for protein engineering, which we coordinate.

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