Conceptual and systems view on gene regulation, text mining assisted information retrieval and biocuration of ‘transcription factor – target gene’ interaction.
I am a molecular biologist with interest in annotation of human chromosomal cis-acting regulatory module DNA sequences. I have produced data on a thousands of epigenetically dynamic transcription promoters and enhancers using primary healthy human white blood cells exposed to beta-glucans, lipopolysaccharide and glucocorticoids. Steroids and other nuclear receptor research interest me very much, as do bHLH and bZIP transcription factors and the signals they integrate and initiate on chromosomes. In summary, I am interested in molecular interactions within chromosomes and how this relates to signalling to the genome and the transcriptional output from the genome.
My expertise is the development of ontologies in different domains. I have developed, for example, an ontology for representing the International classification of diseases (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5064922/) and another ontology for e-commerce and web analytics (http://www.sciencedirect.com/science/article/pii/S0957417416303141). I also developed a scalable OWL reasoner as my PhD Thesis.
I can contribute to the Working Group 1 by providing my knowledge about OWL, RDF, Semantic Web Technologies and Semantic Reasoning.
The focus of the Action is on the development of curation guidelines, ontologies and controlled vocabularies, text mining for triage and data exchange mechanisms to promote computational consumption of knowledge. One of the most serious bottlenecks is the assessment of a formal representation of knowledge that goes beyond PSI-MI (MITAB) and GO (GPAD). Members of the action have posited that semantic web technologies, specifically formal ontologies, may form the basis for a principled solution to this problem. My research focuses on the development of computational methods for scalable integration and reproducible analysis of FAIR (Findable, Accessible, Inleroperable and Reusable) data across biological scales -from molecules, tissues, organs, individuals, populations to the environment. We couple semantic web technologies with machine learning and network analysis to tackle challenging problems in the areas of drug discovery and precision medicine. I am an expert in semantic technologies such as ontologies and linked data, in big data technologies such as scalable indexing and query answering, in domain knowledge of biochemistry and pharmaceutical knowledge. I lead a new Institute for Data Science at Maastricht University, which is co-located with the Maastricht Center for Systems Biology and is adjacent to the Maastricht University Medical Center. I am a Principal Investigator for the NCATS Biomedical Data Translator and a co-Investigator for the NIH BD2K Center for Expanded Data Annotation and Retrieval (CEDAR). I am a member of the Dutch TechCenter for Life Sciences and am a participant in the Dutch node of Elixir, an EU wide initiative to develop a distributed infrastructure for life-science information. I am the editor-in-chief for Data Science and an associate editor for Semantic Web. I am one of two technical leads for the FAIR (Findable, Accessible, Interoperable, Re-usable) data initiative, am the scientific director for Bio2RDF, an open source Linked Data for the life sciences project. I have published over 125 articles in top-rated Journals and international conferences. I am internationally recognized for my contributions in bioinformatics, biomedical informatics, and semantic technologies as evidenced by awards, keynote talks at international conferences, and collaborations on international projects such as this one.
My role in the action is to work with members to explore the feasibility of using semantic web technologies to represent and reason about collective knowledge of gene regulation. As a first step, I will participate in a workshop planned in Malta on April 3-4 and present approaches that we and others have taken to formalize biological and biomedical knowledge, to identify strategies and tactics, to identify challenges and drawbacks. I will highlight our work to transform data from one representation to another and our methods to capture the provenance and evidence of biological assertions. I will work with members to design and evaluate an anontology-based approach to the identified problem. One key outcome will be a new model for the representation of gene regulation knowledge that overcomes the limitations of previous approaches. Another is that we will explore methods to increase the interoperability of gene regulation knowledge by implementing the FAIR principles for this kind of biomedical knowledge. Another key outcome of the workshop is that as a recently recruited researcher to Maastricht University I will strengthen my connections with European researchers and identify new opportunities for collaboration that will lead lo new applications for research funding and the development of impacttul research programs. Indeed, participation in this Action provides a mechanism to involve European researchers in my global research network, particularly that of Canada and the United Stales, as well as currently funded NIH research.