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Orange (www.ailab.si/orange) is a suite for machine learning and data mining. It can be used though scripting in Python or with visual programming in Orange Canvas using GUI components called widgets. In the demonstration we will show how to easily prototype stateof-the-art machine learning algorithms through Orange scripting, and design powerful and(More)
TDP-43 is a predominantly nuclear RNA-binding protein that forms inclusion bodies in frontotemporal lobar degeneration (FTLD) and amyotrophic lateral sclerosis (ALS). The mRNA targets of TDP-43 in the human brain and its role in RNA processing are largely unknown. Using individual nucleotide-resolution ultraviolet cross-linking and immunoprecipitation(More)
In the nucleus of eukaryotic cells, nascent transcripts are associated with heterogeneous nuclear ribonucleoprotein (hnRNP) particles that are nucleated by hnRNP C. Despite their abundance, however, it remained unclear whether these particles control pre-mRNA processing. Here, we developed individual-nucleotide resolution UV cross-linking and(More)
Spam filtering poses a special problem in text categorization, of which the defining characteristic is that filters face an active adversary, which constantly attempts to evade filtering. Since spam evolves continuously and most practical applications are based on online user feedback, the task calls for fast, incremental and robust learning algorithms. In(More)
BACKGROUND The widespread availability of new computational methods and tools for data analysis and predictive modeling requires medical informatics researchers and practitioners to systematically select the most appropriate strategy to cope with clinical prediction problems. In particular, the collection of methods known as 'data mining' offers(More)
Fused in sarcoma (FUS) and TAR DNA-binding protein 43 (TDP-43) are RNA-binding proteins pathogenetically linked to amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD), but it is not known if they regulate the same transcripts. We addressed this question using crosslinking and immunoprecipitation (iCLIP) in mouse brain, which(More)
Janez Demšar JANEZ.DEMSAR@FRI.UNI-LJ.SI Tomaž Curk TOMAZ.CURK@FRI.UNI-LJ.SI Aleš Erjavec ALES.ERJAVE@FRI.UNI-LJ.SI Črt Gorup CRT.GORUP@FRI.UNI-LJ.SI Tomaž Hočevar TOMAZ.HOCEVAR@FRI.UNI-LJ.SI Mitar Milutinovič MITAR.MILUTINOVIC@FRI.UNI-LJ.SI Martin Možina MARTIN.MOZINA@FRI.UNI-LJ.SI Matija Polajnar MATIJA.POLAJNAR@FRI.UNI-LJ.SI Marko Toplak(More)
Besides good predictive performance, the naive Bayesian classifier can also offer a valuable insight into the structure of the training data and effects of the attributes on the class probabilities. This structure may be effectively revealed through visualization of the classifier. We propose a new way to visualize the naive Bayesian model in the form of a(More)
UNLABELLED Visual programming offers an intuitive means of combining known analysis and visualization methods into powerful applications. The system presented here enables users who are not programmers to manage microarray and genomic data flow and to customize their analyses by combining common data analysis tools to fit their needs. AVAILABILITY(More)