our expertise has been published as POC awarded
The technological core of QUIID initially started as a French academic research project. Since 2008, our works have been regularly published in peer-reviewed journals. They’re used as proofs of concept and show how our innovative data mining methods extract new knowledge from databases. Here we provide our major publications.
A Computational Selection of Metabolite Biomarkers Using Emerging Pattern Mining: A Case Study in Human Hepatocellular Carcinoma Article de journal
Dans: Journal of Proteome Research, vol. 0, no. 0, p. null, 2017, (PMID: 28447453).
Discovering structural alerts for mutagenicity using stable emerging molecular patterns Article de journal
Dans: Journal of Chemical Information and Modeling, vol. 0, no. ja, p. null, 2015, (PMID: 25871768).
Automated Detection of Structural Alerts (Chemical Fragments) in (Eco)Toxicology Article de journal
Dans: Computational and Structural Biotechnology Journal, vol. 5, no. 6, p. 1 – 8, 2013, ISSN: 2001-0370.
Emerging Patterns as Structural Alerts for Computational Toxicology Chapitre d’ouvrage
Dans: Chapman and Hall/CRC, 2012, ISBN: 978-1-4398-5432-7, (0).
Extracting and summarizing the frequent emerging graph patterns from a dataset of graphs Article de journal
Dans: Journal of Intelligent Information Systems, vol. 37, no. 3, p. 333-353, 2011, ISSN: 0925-9902.
Introduction of Jumping Fragments in Combination with QSARs for the Assessment of Classification in Ecotoxicology Article de journal
Dans: Journal of Chemical Information and Modeling, vol. 50, no. 8, p. 1330-1339, 2010, (PMID: 20726596).
Discovering Emerging Graph Patterns from Chemicals Recueil
Dans: Rauch, Jan; Raś, ZbigniewW.; Berka, Petr; Elomaa, Tapio (Ed.): Foundations of Intelligent Systems, vol. 5722, p. 45-55, Springer Berlin Heidelberg, 2009, ISBN: 978-3-642-04124-2.