Python is an open-source, object-oriented programming language, particularly well-suited for scientific computing because of its extensive ecosystem of scientific libraries and environments. For more information, see the Python FAQ page and the Python Numeric and Scientific Wiki.
High Performance Workstation 4 (PC)
The Data Sciences workspace at the NIH Library is available as part of the Library's Technology Hub. The Data Sciences Workspace provides a suite of tools for data analysis, processing, and visualization, useful for a variety of different types of data. The workspace also includes links to information on using data tools, conducting research using data mining, and finding data available for re-use. This guide provides an introduction to the software packages available and provides a quick guide to getting started, and consultations and tutorials are available for users who would like to learn how to use software, access data from the Clinical Center’s BTRIS system, or conduct other types of data-intensive research.
ArcGIS Desktop/Pro/Spatial Analysis
Provides basic tools to analyze your data and author geographic knowledge to examine relationships, test predictions, and ultimately make better decisions.
Supports data visualization, advanced analysis and authoritative data maintenance in both 2D and 3D. ArcGIS Pro supports data sharing across ArcGIS Online and ArcGIS Enterprise through Web GIS.
Cytoscape (Open Source, Freely Available)
Cytoscape is a free, open source visualization tool for modeling complex networks and integrating network points with attribute data. Cytoscape can create visualizations of a variety of different types of networks, including molecular and genetic, social networks, and semantic Web. Adding free plugins to Cytoscape also provides functionality including literature mining, network inference, topological clustering, and network comparison.
Github Desktop
GitHub is a platform for storing and collaborating on code. GitHub Desktop is an application that enables you to interact with GitHub using a GUI instead of the command line or a web browser. Learn more at GitHub Docs.
GraphPad Prism
GraphPad Prism is an analysis and graphing software for scientific research. To learn more, visit the GraphPad Knowledgebase.
JMP (Statistics software)
JMP is the data analysis tool of choice for hundreds of thousands of scientists, engineers and other data explorers worldwide. Users leverage powerful statistical and analytic capabilities in JMP to discover the unexpected. With JMP you can perform data analysis, data acquisition and cleanup, data visualization, reliability analysis, text exploration, statistical modeling, and it integrates with SAS, MATLAB, and R.
MATLAB
MATLAB is a programming and numeric computing platform used to analyze data, develop algorithms, and create models. In addition to MATLAB, we also license the Deep Learning (NNSMS)
and Statistics and Machine Learning (STSMS) toolboxes.
R and RStudio (Open Source, Freely Available)
R and R Studio are useful for a wide variety of data manipulation, analysis, and visualization tasks.
SAS (Base)
Base SAS includes a programming language that manages your data, includes procedures for data analysis, reporting, and managing SAS files, and a windowing environment for text editing and file management.
SPSS Statistics
IBM SPSS Statistics enables you to quickly dig deeper into your data, making it a much more effective tool than spreadsheets, databases or standard multi-dimensional tools for analysts. SPSS Statistics includes a variety of functionalities such as descriptive statistics, data preparation, graphing, bivariate statistics procedures, factor and cluster analysis and linear and ordinal regression.
Stata
Stata is an integrated statistical software package for data management, analysis, and visualization.
Tableau Desktop
Tableau is a business analytics tool for creating a wide variety of interactive data visualizations.
VosViewer (Freely Available)
VOSviewer is a free software tool for constructing and visualizing bibliometric networks.