Qtmib
qtmib is an open-source molecular visualization and analysis software for proteins and small molecules. It provides 2D and 3D visualizations, sequence alignment, Ramachandran plots, and other common analyses.
visualization
analysis
proteins
small-molecules
3d
2d
sequence-alignment
ramachandran-plots
qtmib: Open-Source Molecular Visualization and Analysis Software
qtmib is an open-source molecular visualization and analysis software for proteins and small molecules. It provides 2D and 3D visualizations, sequence alignment, Ramachandran plots, and other common analyses.
What is Qtmib?
qtmib is an open-source molecular visualization and analysis software for proteins and small molecules. It is cross-platform and provides an intuitive graphical user interface for common structural bioinformatics workflows.
Key features of qtibm include:
- Visualization of protein structures and small molecules in 2D and 3D
- Interactive Ramachandran plots for assessing protein backbone conformations
- Sequence alignment and analysis tools
- Integration of external web services like BLAST and HHpred for remote homology detection
- Python scripting interface for automation and customization
- Support for a wide range of common structure and sequence file formats
As an open-source solution, qtmib enables free use, modification, and distribution to suit specialized research needs. It offers scientists an accessible workflow for molecular modeling and structure analysis without expensive licensing or proprietary frameworks.
The focus on usability, extensibility, and standard bioinformatics formats makes qtmib well-suited for research groups looking for a no-cost visual analytics program for structural biology and chemistry.
Qtmib Features
Features
- 2D and 3D molecular visualization
- Protein and small molecule modeling
- Sequence alignment
- Ramachandran plots
- Common molecular analysis tools
Pricing
- Open Source
Pros
Open source
Intuitive graphical interface
Support for major structural biology file formats
Plugin architecture for extensibility
Cross-platform compatibility
Cons
Limited built-in statistical analysis features
Steep learning curve for advanced features
Not as feature rich as commercial alternatives
Official Links
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