Johan T den Dunnen, Human & Clinical Genetics, Leiden University Medical Center, Leiden, studied biology at the Catholic University Nijmegen (Nederland). In the same university he received his PhD in Molecular Biology for his work on the "Evolution of eye-lens crystallin genes" (promoter Prof.dr. JGG Schoenmakers). After his PhD he changed to the department of Human Genetics (head Prof.dr. PL Pearson), Leiden University, and became involved in the search for the gene causing Duchenne and Becker muscular dystrophy. He is currently employed at the Center for Human and Clinical Genetics (head Prof.dr. GJB van Ommen, Leiden University Medical Center, Leiden, Nederland), studying genetic disease in general and neuromuscular disorders (DMD/BMD, LGMD) in particular. As professor in "Medical Genome Technology" he focuses on the use of new high-throughput genome technology in research and diagnosis of genetic disease, in particular the development and innovation of mutation detection technologies and the application of next generation sequencing. To spread the laboratories knowledge on hereditary muscle disease he initiated the "Leiden Muscular Dystrophy pages" (http://www.DMD.nl). As part of these efforts he currently curates over 50 gene sequence variant databases. His group developed the freely available LSDB-in-a-Box software package LOVD, the Mutalyzer tool (HGVS mutation nomenclature description) and he participates in the EU FP7 Gen2Phen project (WP leader for LSDBs).
Shortly after its start Johan joined the HUGO Mutation Database Initiative and he is a board member of the Human Genome Variation Society since its initiation in 2002. He gradually became involved in the society's activities to establish uniform rules for the description of DNA sequence variants (mutation nomenclature) and currently acts as the secretary on this subject. As such, he curates the society's mutation nomenclature web pages, answers all questions on the topic and promotes the HGVS' goals in presentations on mutation detection and gene sequence variant databases.