AMC, Department of Clinicial Epidemiology, Biostatistics and Bioinformatics (KEBB)
Meibergdreef 9, 1105 AZ Amsterdam
Prof. dr. A.H.C. van Kampen
0031 (0)20 5667096
The Bioinformatics Laboratory focuses on the development and application of bioinformatics methods in life sciences. Our group has prominent tasks in research, education and support of life scientists with the analysis and management of their omics datasets. The Bioinformatics Laboratory is one of the Core Research Facilities in the AMC.
The support facility harbors 15 years of expertise in the (statistical) analysis of e.g., microarray data (e.g., expression, methylation, SNPs), NGS (genomes, exomes, RNAseq, SNPs, Chipseq, etc), and LC-MS metabolomics data. Moreover, we have large experience with the use and integration of public biological databases. To a lesser extent we are involved in the analysis of proteomics data. A range of methods and pipelines are available to perform data analysis. In addition, we provide assistance on experimental design.
Our research is centered on systems genomics (e.g., network alignment, (multi-scale) mathematical modeling, and pathway analysis) and OMICS data analysis. Methods and expertise developed as part of our research provide further input for support projects.
We are closely connected to AMC omics facilities for (next generation) sequencing, metabolomics/lipidomics, and proteomics which provides us with knowledge about all experimental procedures and issues relevant for the bioinformatics analysis.
Throughout the years we have support a large range of projects of (AMC) groups comprising a wide range of biomedical questions and study designs.
- Biomedical & health
- Next Generation Sequencing, whole genome/exome sequencing, RNAseq, miRNAs
- Genomics, Transcriptomics, Proteomics, Metabolomics, Bioinformatics, Systems Medicine
- Use and Integration of public biological data
- Experimental Design
- Human disease: genetics, immunology, cardiovascular, infection, metabolic, etc
- Metabolomics and Lipidomics
- Human and model organisms
- Mathematical modelling of immune systems
- Applied and Fundamental research
Expertise and Track Record
435000030 Trans-acting (epi)genetic regulation of gene expression associated with aortic aneurysm in patients with Marfan syndrome with dr. P.D. Moerland (AMC). 435002030 Characterization of N-glycoslyation sites in the B cell receptor reportoire of auto-reactive, citrullinated antigen-specific B cells With Scherer (LUMC).
Having over 15 years of experience in bioinformatics research and support, we now provide expertise and methodologies that covers a wide range of omics data types, (disease) applications, and bioinformatics methodologies. Our group is also closely linked to clinical research and AMC omics facilities. We have been engaged in a large number of biomedical projects with many different research groups.
The Bioinformatics Laboratory has more than 15 years of experience in providing bioinformatics support to groups within and outside the AMC. We cover most omics areas. Support includes (statistical) data analysis, usage and integration of public databases, providing access to e-infrastructures, etc. We typically conduct many support projects in parallel.
Typical support projects include:
Analysis of datasets from a range of platforms and diseases. For example, miRNA (Schopman (2012), Nucleic Acids Research, 40(1), 414), exome (e.g., Van Houdt (2012) Nature Genetics, 44(4), 445), microarrays (Bergonzi (2013) Science, 340(6136), 1094), and lipidomics (Wortmann (2012) Nature Genetics, 44(7), 797-802)
- Stobbe MD, Houten SM, van Kampen AH, Wanders RJ, Moerland PD. (2012) Improving the description of metabolic networks: the TCA cycle as example. FASEB Journal, 26(9), 3625-36. a. This is one of the publications from our system genomics research line in which we analysed and compared a large range of public pathway databases to reveal how they differ for a well-known pathway in order to provide pointers for further research in both the development of such databases as well as experiments to further delineate this pathway. b. This work also resulted in a publicly available tool that that can be used for the curation of existing pathway databases (www.c2cards.nl)
- Klarenbeek PL, de Hair MJ, Doorenspleet ME, van Schaik BD, Esveldt RE, van de Sande MG, Cantaert T, Gerlag DM, Baeten D, van Kampen AH, Baas F, Tak PP, de Vries N. (2012) Inflamed target tissue provides a specific niche for highly expanded T-cell clones in early human autoimmune disease. Annals of the Rheumatic Diseases, 71(6), 1088-93. a. This publication highlights a novel wet-lab and bioinformatics protocol that was developed in this collaboration for the sequence analysis of T cell receptors. The approach that we developed to analyze the T-cell receptor reportoire (and that of B cell receptors) is increasingly attracting attention.
- HMJ Sontrop, WFJ Verhaegh, MJT Reinders, PD Moerland. (2011) Evaluation strategies for subtype-specific breast cancer event prediction. PLoS ONE a. This paper exemplifies our work on developing reliable omics-based predictors for diagnosis and prognosis. We developed a novel protocol for the proper comparison and evaluation of predictors for diseases that consist of distinct subtypes such as breast cancer. Comparing different models on a compendium of breast cancer gene expression datasets showed that predictors based on subtyped models outperform untyped predictors.
- Luyf AC, van Schaik BD, de Vries M, Baas F, van Kampen AH, Olabarriaga SD. (2010) Initial steps towards a production platform for DNA sequence analysis on the grid. BMC Bioinformatics. 11(1), 598. a. This paper provides a typical example of our approach to making e-Science technologies routinely available for the life scientists (in this case for NGS analysis) b. The underlying infrastructure (e-Bioinfra) is now routinely used in many of our sequence analysis projects (including the T and B cell projects mentioned above)
- Doorenspleet ME, Klarenbeek PL, de Hair MJ, van Schaik BD, Esveldt RE, van Kampen AH, Gerlag DM, Musters A, Baas F, Tak PP, de Vries N. Rheumatoid arthritis synovial tissue harbours dominant B-cell and plasma-cell clones associated with autoreactivity. Ann Rheum Dis. 2014 Apr;73(4):756-62
- Cordeddu V, Redeker B, Stellacci E, Jongejan A, Fragale A, Bradley TE, Anselmi M, Ciolfi A, Cecchetti S, Muto V, Bernardini L, Azage M, Carvalho DR, Espay AJ, Male A, Molin AM, Posmyk R, Battisti C, Casertano A, Melis D, van Kampen A, Baas F, Mannens MM, Bocchinfuso G, Stella L, Tartaglia M, Hennekam RC. Mutations in ZBTB20 cause Primrose syndrome. Nat Genet. 2014 Aug;46(8):815-7
Netherlands Bioinformatics Center (research);Netherlands Center for Systems Biology (research);
- 2 FTE Dedicated postdocs
- 2 FTE Bioinformaticians
- 1 FTE group leader
- 1 FTE Support/Research
- x FTE Research
- ICT infrastructure, Storage, compute facilities,
- We make use of SURFsara facilities for compute
Depends on project. For example GEO @NCBI