Search Results for "interface"

...It supports both over-representation analysis and gene set enrichment analysis, letting you work with unranked gene lists or ranked statistics from differential pipelines. The package connects to multiple knowledge bases—such as Gene Ontology, KEGG, Reactome, Disease Ontology, MeSH and others—through a consistent interface so you can query different biological lenses without rewriting code. It is designed for breadth, covering coding and non-coding features and thousands of organisms by leveraging continuously updated annotations. Results are returned in tidy, manipulation-friendly structures and pair naturally with rich visualization functions (via companion tooling) to summarize pathways, terms, and gene–set relationships.

SADSA (Software Application for Data Science and Analytics) is a Python-based desktop application designed to simplify statistical analysis, machine learning, and data visualization for students, researchers, and data professionals. Built using Python for the GUI, SADSA provides a menu-driven interface for handling datasets, applying transformations, running advanced statistical tests, machine learning algorithms, and generating insightful plots — all without writing code.

...The application provides data visualization tools, including box plots for distribution analysis and scatter plots for exploring relationships between variables. Users can download the processed data for further analysis. Built with Tkinter, Pandas, Matplotlib, and Seaborn, it ensures an intuitive interface and efficient performance. Additionally, it features a custom logo, a clean UI with a green-blue theme, and options for licensing and public release. This tool is ideal for data analysts, researchers, and professionals looking to automate preprocessing without coding. 🚀

SciDAVis is a user-friendly data analysis and visualization program primarily aimed at high-quality plotting of scientific data. It strives to combine an intuitive, easy-to-use graphical user interface with powerful features such as Python scriptability.

While resting-state fMRI is drawing more and more attention, there has not been a software for its data analysis. Based on MATLAB, we developed a package named REST. Currently REST has three main functions: function connectivity, ReHo and ALFF.

GEDAS is a software to perform microarray data analysis with friendly user interface and convenient data display. Currently some commonly used data clustering algorithms have been implemented in this software.

ModuleFair is a generic, module-based framework upon which to quickly build anything from data analysis programs to game level editors. This project is no longer maintained.