Erik van Mulligen

BioRelated/Noteworthy Publications
Eun Kyoung Ahn

Erik M. van Mulligen
Assistant Professor, Dept of Medical Informatics
Erasmus University Medical Center

Dr. Erik M. van Mulligen graduated at the Free University of Amsterdam in Mathematics and Computer Science and specialised in medical informatics and artificial intelligence. His MSc work focused on (mathematical) reconstruction of vector cardiograms from the standard 12-lead electrocardiogram. He received his PhD from the Erasmus University on computer architectures for integrated medical workstations. He organized a conference on software engineering in medical informatics (SEMI). He has been involved in a number of EU projects (3rd, 4th, 5th, 6th and 7th Telematics Programme of DGXIII and Horizon 2020). He collaborated with international institutes and obtained in 1995 a two-year fellowship at the National Library of Medicine for working at the cognitive science branch on UMLS-based research on thesaurus-based searches in computer-based patient record systems.

After his fellowship, he returned to the department of Medical Informatics of the Erasmus University. He was involved in research projects aiming at structured computer-based patient records. From 2002 on he has been working in the field of bio-semantics focusing on (semantic) text mining, both as CTO of the Collexis software company and at the department of Medical Informatics at Erasmus University Medical Center. In 2005, he joined Knewco Inc, an American company in the field of semantic text analysis as CTO. Currently, Erik van Mulligen is an assistant professor at the department of Medical Informatics at the Erasmus University Medical Center on bio-semantics and works as a senior consultant for Science and Technology Corp.

His particular professional interest is in natural language processing (in particular concept recognition / named entity recognition), ontologies and machine learning. Erik is working on machine translation of the OHDSI CDM to Dutch and applied an initial version to text mining of Dutch clinical notes.

Using predicate and provenance information from a knowledge graph for drug efficacy screening. Vlietstra WJ, Vos R, Sijbers AM, van Mulligen EM, Kors J, J Biomed Sem 9-23, 2018

The FAIR Guiding Principles for scientific data management and stewardship. Wilkinson M. et. al. Nature Scientific Data, March 2016.

Interoperability and FAIRness through a novel combination of Web technologies. Mark D. Wilkinson et. al. PeerJ Computer Science 3(Suppl 1):e110 doi 10.7717/peerj-cs.110

Automated extraction of potential migraine biomarkers using a semantic graph. Vlietstra WJ, Zielman R, van Dongen RM, Schultes EA, Wiesman F, Vos R, van Mulligen EM, Kors JA. J Biomed Inform. 2017 Jul;71:178-189. doi: 10.1016/j.jbi.2017.05.018. Epub 2017 Jun 1.

Finding potentially new multimorbidity patterns of psychiatric and somatic diseases: exploring the use of literature-based discovery in primary care research. Vos R, Aarts S, van Mulligen E, Metsemakers J, van Boxtel MP, Verhey F, van den Akker M. J Am Med Inform Assoc. 2014 Jan-Feb;21(1):139-45. doi: 10.1136/amiajnl-2012-001448.

A novel feature-based approach to extract drug-drug interactions from biomedical text. Bui QC, Sloot PMA, van Mulligen EM, Kors JA. Bioinformatics, Aug 2014

Calling on a million minds for community annotation in WikiProteins. Mons B, Ashburner M, Chichester C, van Mulligen E, Weeber M, den Dunnen J, van Ommen GJ, Musen M, Cockerill M, Hermjakob H, Mons A, Packer A, Pacheco R, Lewis S, Berkeley A, Melton W, Barris N, Wales J, Meijssen G, Moeller E, Roes PJ, Borner K, Bairoch A. Genome Biol. 2008

Concept Recognition and Coding in French Texts. Erik M. van Mulligen, Zubair Afzal, Saber A. Akhondi, Dang Vo, and Jan A. Kors. CLEF eHealth proceedings, Sept 2016.

Evaluation of a multinational, multilingual vaccine debate on Twitter. Becker, B. F., Larson, H. J., Bonhoeffer, J., van Mulligen, E. M., Kors, J. & Sturkenboom, M. C., Vaccine 34(50):6166-71, 2016

Extraction of chemical-induced diseases using prior knowledge and textual information. Pons E. Becker BFH, Akhondi SA, Afzal Z, van Mulligen EM, Kors JA. Database (2016) Vol. 2016: article ID baw046;doi:10.1093/database/baw046.

Evaluating Social Media Networks in Medicines Safety Surveillance: Two Case Studies. Coloma PM, Becker BFH, Sturkenboom MCHM, van Mulligen EM, Kors JA. Drug Safety, Aug 2015

Automatic vs. manual curation of a multi-source chemical dictionary: the impact on text mining. Hettne KM, Williams AJ, van Mulligen EM, Kleinjans J, Tkachenko V, Kors JA. J Cheminform. March 2010

CALBC silver standard corpus. Rebholz-Schuhmann D, Yepes AJ, Van Mulligen EM, Kang N, Kors J, Milward D, Corbett P, Buyko E, Beisswanger E, Hahn U. J Bioinform Comput Biol. February 2010

Novel protein-protein interactions inferred from literature context. van Haagen HH, ‘t Hoen PA, Botelho Bovo A, de Morrae A, van Mulligen EM, Chichester C, Kors JA, den Dunnen JT, van Ommen GJ, van der Maarel SM, Kern VM, Mons B, Schuemie MJ. PLoS One. November 2009

Knowledge-based extraction of adverse drug events from biomedical text. Ning Kang, Bharat Singh, Chinh Bui, Zubair Afzal, Erik M van Mulligen, Jan A Kors. BMC BioInformatics March 2014.