Antoine van Kampen heads the Bioinformatics Laboratory ( www.bioinformaticslaboratory.nl) at the AMC (www.amc.nl) and holds the chair Biological and Biomedical Information Science with a special focus on Medical Bioinformatics. This chair is established by the Genootschap ter bevordering van natuur-, genees- en heelkunde (gngh.uva.nl) together with the Faculty of Science. Van Kampen has a parttime position in the Biosystems Data Analysis group (www.bdagroup.nl) of the Swammerdam Institute for Life Sciences (SILS) of the University of Amsterdam (UvA) to facilitate collaborations between the AMC and the Science Faculty. Van Kampen was scientific director of the Netherlands Bioinformatics Center (NBIC) from 2006 - 2010. Here he was responsible for budgets (>50 MEuro) and the initiation, stimulation, and coordination of bioinformatics programmes in research, support, e-bioscience infrastructure, and education.
Van Kampen has a background in chemometrics and did his PhD at the Laboratory for Analytical Chemistry (Prof. dr. Lutgarde Buydens; University of Nijmegen) where he worked on the development of global optimization techniques and their application in chemistry (e.g. protein structure determination from NMR, classification of ion chromatography methods). Part of this work was conducted at the laboratories for Analytical Chemistry (prof. dr. Brynn Hibbert) and Artificial Intelligence (Prof. dr. Paul Compton) at the University of New South Wales (Sydney). In 1997 he received the Clemens Rothaan price from the section "computertoepassingen" of the Royal Netherlands Chemical Society (KNCV) for his research. After a short post-doc period on the project 'Computer supported education' he moved to the Academic Medical Center (AMC) in Amsterdam. There he started bioinformatics research and initiated the Bioinformatics Laboratory of which he became head.
The Systems Genomics and Systems Medicine research line research comprises the development and application of methods for the analysis of biological systems. Part of the projects are directed towards immunology. We focus on the analysis of T and B cell responses in autoimmune disorders by analysing the lymphocyte repertoire through RNA sequencing of T and B cell receptors (Klarenbeek, Immunology Letters, 2010). Concurrently, we aim to develop improved methods for the reconstruction of B cell lineage trees from this data to gain insight in these B cell responses (in prep). To increases our understanding of the various biological parameters involved in these responses we develop differential equation based mathematical models of the germinal center reaction. In a collaboration with GSK we aim to develop novel methods for the integration of gene expression data and other (clinical) immunological readouts to compare and characterize vaccine adjuvants. We also work on the development of computational methods to uncover perturbed molecular (disease) networks. Examples of such projects comprise (a) the investigation of similarities and differences between mouse models and human using through the alignment of gene co-expression networks (in prep), (b) the use of Petri Nets to study multi-organ elimination pathways (in prep), and (c) the development and application of metDFBA to study metabolic fluxes in non-steady state systems (Willemsen, Molecular Biosystems, 2014).
Petri net model of the human genistein multi-compartment elimination pathway. This model includes three metabolites (G - genistein, GG; genistein-7-glucuronide; S - genistein-7-glucuronide-4-sulphate) that travel within and between six compartments (organs, blood). G(I) is the input place. Each transition is associated with a fraction (F) indirectly representing a flux.
The information management research line comprise projects that involve the use of public biological database and development of knowledgebases. The collection of prior biological knowledge, e.g., published information about biochemical pathways is another key component in systems medicine research. We recently performed a systematic comparison of five comprehensive and often used metabolic networks and uncovered surprisingly large differences between these databases (Stobbe, BMC Systems Biology, 2011; Stobbe, Briefings in Bioinformatics, 2014). In other research we focussed on the development of a knowledgebase framework for the integration and presentation peroxisome domain knowledge (Willemsen, Bioinformatics, 2008).
Example of a concept map showing the four key peroxisomal pathways in our knowledge base. Icons associated with specific concepts provide links to other concept maps or information resources (pdf documents).
The e-Bioscience research line focusses on the development of e-Science gateways and research data management. Advanced distributed data and computing infrastructures, also known as e-infrastructures, enable biomedical researchers to manage and process (omics) data and facilitate collaboration. However, these researchers often do not have the advanced technical knowledge that is required to fully exploit these advanced infrastructures. Science Gateways (SGs) have emerged to address this challenge. Our research focussed on the investigation, design, development and evaluation of state-of-the-art SGs to access e-infrastructures for biomedical research (Shahand, Journal of Grid Computing, 2012; Shahand, Concurrency and Computation: Practice and Experience, 2012). Currently we are aim to extend our SG framework for research data management while focussing on immunology research as a test case.
Three components of a Science Gateway.
In addition to these three research lines, we are involved in many other research projects such as exome sequencing (Van Houdt, Nature Genetics, 2012; Cordeddu, Nature Genetics, 2014), pre-processing of LC-MS metabolomics data (Wortmann, Nature Genetics, 2012; Vaz, Journal of Inherited Metabolic Disease, 2015) and RNAseq (Backer, Nature Immunology, 2014).
Van Kampen is involved in a large range of bioinformatics/systems biology teaching and training activities. He is currently involved in several bachelor and master programs: medical informatics program (AMC), biomedical sciences (SILS), Computational Sciences (Institute for Informatics, UvA), Bioinformatics and Systems Biology (VU University Amsterdam). As part of the bachelor biomedical sciences program he coordinates the 12 EC course Genomics of Disease in which students are introduced to omics technologies, bioinformatics and systems biology. At the AMC he initiated and/or coordinates several courses as part of the AMC Graduate School for PhD students: Unix, Bioinformatics, Bioinformatics for sequence analysis, and Systems Medicine.