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RNA secondary structure as a reusable interface to biological information resources
R M Felciano1, R O Chen, R B Altman
1Section on Medical Informatics, Stanford University, CA 94305-5479, USA. felciano@smi.stanford.edu
Gene
|May 6, 1997
Summary
Biological information access is enhanced by sophisticated web interfaces. This study introduces reusable "domain graphics," like RNA secondary structure layouts, for intuitive biologist-computer interaction, improving data exploration and tool integration.
Area of Science:
- Bioinformatics
- Computational Biology
- Web Technologies
Background:
- Biological information dissemination increasingly relies on the Internet and World Wide Web (WWW).
- Current biologist-web interactions are often limited to basic interfaces like hypertext links and forms.
- Sophisticated WWW-based user interfaces are enabled by platform-independent runtime environments.
Purpose of the Study:
- To develop reusable, sophisticated WWW-based user interfaces for biological information.
- To leverage intuitive graphical representations of biological knowledge, termed "domain graphics," as interface elements.
- To demonstrate the versatility of domain graphics by creating an RNA secondary structure interface.
Main Methods:
- Developed a reusable interface based on the standard two-dimensional (2D) layout of RNA secondary structure.
- Designed the interface to represent pre-computed RNA layouts and accept user interaction parameters.
- Enabled the interface to provide information about selected bases, helices, or subsequences to associated applications.
Main Results:
- Created a versatile interface adaptable to various RNA data.
- Demonstrated the interface's utility as a specialized front-end for BLAST, Medline, and RNA MFOLD.
- Showcased the potential of domain graphics for intuitive biological data exploration.
Conclusions:
- Domain graphics offer a powerful approach for creating multipurpose, intuitive WWW-based biological user interfaces.
- Reusable graphical components can be effectively integrated with existing biological databases and computational engines.
- This approach enhances biologist interaction with complex biological information and computational tools.