Background and activities
The Kuiper lab focuses on the use of ontologies and semantic web technologies for the integration and exploration of biological knowledge.
Martin Kuiper received a M.Sc. degree in Molecular Biology and Biochemistry (1982), and a PhD degree (1987) in Biology from the University of Groningen, Netherlands. He was a doctoral fellow of the Ohio State University, US (1987) and Utrecht University, Netherlands (1989). He then took a career change and went to industry, where he worked at KeyGene NV, the Netherlands; GenScope bvba / Celera West, Belgium / California; and Aventis CropScience, Belgium. After 9 years in industry he joined the VIB institute in Gent, Belgium, as PI in Computational Biology. He transferred to the Norwegian University of Science and Technology in 2008, where he now works as Professor in Systems Biology. His research interests include the development of approaches and tools for analysis of biological data, and the use of ontologies and semantic web technologies for integration of biological knowledge. Together with colleagues from the Faculty of Medicine and Faculty of Humanities he is involved in three sub-projects of the DrugLogics initiative (www.DrugLogics-NTNU.org), targeting Responsible Research and Innovation (RRI): Crossover Research 2.0; Rational development of anti-cancer drug combinations and the modeling of drug resistance in colon cancer (the ERACoSysMed project COLOSYS).
Scientific, academic and artistic work
A selection of recent journal publications, artistic productions, books, including book and report excerpts. See all publications in the database
- (2019) Scientific knowledge in the age of computation: Explicated, computable and manageable?. Theoria. An international Journal of Theory, History and Foundations of Science.
- (2019) CausalTAB: the PSI-MITAB 2.8 updated format for signalling data representation and dissemination. Bioinformatics.
- (2019) The Gene Ontology Resource: 20 years and still GOing strong. Nucleic Acids Research.
- (2016) Genes2GO: A web application for querying gene sets for specific GO terms. Bioinformation. vol. 12 (3).
- (2016) Gene regulation knowledge commons: community action takes care of DNA binding transcription factors. Database: The Journal of Biological Databases and Curation.
- (2015) Discovery of Drug Synergies in Gastric Cancer Cells Predicted by Logical Modeling. PloS Computational Biology. vol. 11 (8).
- (2015) Sequence-Dependent Promoter Escape Efficiency Is Strongly Influenced by Bias for the Pretranslocated State during Initial Transcription. Biochemistry. vol. 54 (28).
- (2014) Using the relation ontology Metarel for modelling Linked Data as multi-digraphs. Semantic Web. vol. 5 (2).
- (2014) Design of a Minimal System for Self-replication of Rectangular Patterns of DNA Tiles. Lecture Notes in Computer Science. vol. 8890.
- (2014) OrthAgogue: An agile tool for the rapid prediction of orthology relations. Bioinformatics. vol. 30 (5).
- (2014) Finding gene regulatory network candidates using the gene expression knowledge base. BMC Bioinformatics. vol. 15 (1).
- (2013) The emergence of Semantic Systems Biology. New Biotechnology. vol. 30 (3).
- (2013) TFcheckpoint: a curated compendium of specific DNA-binding RNA polymerase II transcription factors. Bioinformatics. vol. 29 (19).
- (2013) Label-Free Quantitative Proteomic Analysis of Systemic Responses to Local Wounding and Virus Infection in Arabidopsis thaliana. Journal of Proteome Research. vol. 12 (6).
- (2013) Gene Ontology annotation of sequence-specific DNA binding transcription factors: setting the stage for a large-scale curation effort. Database: The Journal of Biological Databases and Curation.
- (2012) Gauging triple stores with actual biological data. BMC Bioinformatics. vol. 13.
- (2012) Jointly creating digital abstracts: dealing with synonymy and polysemy. BMC Research Notes. vol. 5 (601).
- (2012) OLSVis: an animated, interactive visual browser for bio-ontologies. BMC Bioinformatics. vol. 13.
- (2011) Contributions of the EMERALD project to assessing and improving microarray data quality. BioTechniques. vol. 50 (1).