Topic: biological-sequences-analysis Goto Github

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superzchen / ifeatureomega-cli
biological-sequences-analysis,iFeatureOmega is a comprehensive platform for generating, analyzing and visualizing more than 170 representations for biological sequences, 3D structures and ligands. To the best of our knowledge, iFeatureOmega supplies the largest number of feature extraction and analysis approaches for most molecule types compared to other pipelines. Three versions (i.e. iFeatureOmega-Web, iFeatureOmega-GUI and iFeatureOmega-CLI) of iFeatureOmega have been made available to cater to both experienced bioinformaticians and biologists with limited programming expertise. iFeatureOmega also expands its functionality by integrating 15 feature analysis algorithms (including ten cluster algorithms, three dimensionality reduction algorithms and two feature normalization algorithms) and providing nine types of interactive plots for statistical features visualization (including histogram, kernel density plot, heatmap, boxplot, line chart, scatter plot, circular plot, protein three dimensional structure plot and ligand structure plot). iFeatureOmega is an open-source platform for academic purposes. The web server can be accessed through http://ifeature2.erc.monash.edu and the GUI and CLI versions can be download at: https://github.com/Superzchen/iFeatureOmega-GUI and https://github.com/Superzchen/iFeatureOmega-CLI, respectively.
User: superzchen
python feature-engineering bioinformatics-tool biological-data-visualization feature-analysis biological-sequences-analysis

superzchen / ifeatureomega-gui
biological-sequences-analysis,iFeatureOmega is a comprehensive platform for generating, analyzing and visualizing more than 170 representations for biological sequences, 3D structures and ligands. To the best of our knowledge, iFeatureOmega supplies the largest number of feature extraction and analysis approaches for most molecule types compared to other pipelines. Three versions (i.e. iFeatureOmega-Web, iFeatureOmega-GUI and iFeatureOmega-CLI) of iFeatureOmega have been made available to cater to both experienced bioinformaticians and biologists with limited programming expertise. iFeatureOmega also expands its functionality by integrating 15 feature analysis algorithms (including ten cluster algorithms, three dimensionality reduction algorithms and two feature normalization algorithms) and providing nine types of interactive plots for statistical features visualization (including histogram, kernel density plot, heatmap, boxplot, line chart, scatter plot, circular plot, protein three dimensional structure plot and ligand structure plot). iFeatureOmega is an open-source platform for academic purposes. The web server can be accessed through http://ifeature2.erc.monash.edu and the GUI and CLI versions can be download at: https://github.com/Superzchen/iFeatureOmega-GUI and https://github.com/Superzchen/iFeatureOmega-CLI, respectively.
User: superzchen
python feature-engineering biological-sequences-analysis bioinformatics-tool feature-analysis biological-data-visualization