SUPPLEMENTARY MATERIAL: VisuNet: an interactive tool for rule network visualization of rule-based learning models
The data consists of a pdf file with visualizations and an excel file with following tables: - Table S1 The overview of applications. - Table S2 SFARI result for 4 genes overlapped the rule-network of case-control study of autism and the SFARI genes databese. - Table S3 GO over-representation results for the rule-network of case-control study of autism. - Table S4 Full list of variables used for the rule-based machine learning schema. The list includesmetabolites and pools of metabolites. - Table S5 List of rules for the R.ROSETTA model including support, accuracy and BH-corrected p-value for each rule. The dataset was originally published in DiVA and moved to SND in 2024.
Department of Cell and Molecular Biology, Computational Biology and Bioinformatics / Science for Life Laboratory, SciLifeLab
Department of Cell and Molecular Biology, Computational Biology and Bioinformatics
Department of Cell and Molecular Biology, Computational Biology and Bioinformatics, Department of Immunology, Genetics and Pathology / Science for Life Laboratory, SciLifeLab
The Grenoble Institute of Technology– Phelma
Uppsala University / University of Cambridge
Department of Medical Biochemistry and Microbiology, Department of Cell and Molecular Biology / Cancer Research UK Cambridge Institute
Uppsala University, Swedish Collegium for Advanced Study (SCAS)
Bioinformatics and Computational Biology
Avser insamling, behandling och analys av biologisk och medicinsk information.