Approximate multiple kernel learning with least-angle regression
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Martin Stražar received a masters and a doctoral degree in computer science from University of Ljubljana, Faculty of Computer and Information Science in 2013 and 2018, respectively.
His research interest span scalable machine learning, data integration, kernel methods and Bayesian statistics. The main applications of the developed models are in bioinformatics: modelling with next-generation sequencing (NGS) data sets, protein-RNA iterations and single-cell RNA sequencing.
Dr. Stražar was the recipient of the 2012 iGEM Best Health and Medicine prize, and 2012 iGEM Best Modelling prize. He is one of the core contributors of data mining software platforms Orange (https://orange.biolab.si) and Single cell Orange (https://singlecell.biolab.si).
Tomaž Curk received a doctoral degree in computer science from the University of Ljubljana, Faculty of Computer and Information Science in 2007.
His research interest include bioinformatics, machine learning and data integration, with applications in modelling RNA-seq data on gene expression and iCLIP and RBDmap data on protein-RNA interaction.
Dr. Curk serves as Vice-Dean for research at the Faculty of Computer and Information Science from 2016. He is one of the initial contributors to the data mining software Orange (http://orange.biolab.si), gene expression analysis software dictyExpress (http://dictyexpress.org), gene interaction analysis software SNPsyn (http://snpsyn.biolab.si) and of the iCount software for protein-RNA interaction analytics (https://github.com/tomazc/iCount).