Short answer
For complex data platforms, continuously expand content, offer multiple access points, and embed analytical tools to maximize user engagement and research utility.
- Field
- User-Centred Design
- Source
- Nucleic Acids Research (2021)
- Method
- Database expansion and feature development
- Evidence
- Strong effect
The 9th release of JASPAR significantly expands its collection of transcription factor binding profiles and introduces new tools and access methods, enhancing its utility for researchers. This user-centred design research insight is drawn from a 2021 study published in Nucleic Acids Research. Using Database expansion and feature development, researchers explored how this design variable affects real-world outcomes. The key design takeaway: For complex data platforms, continuously expand content, offer multiple access points, and embed analytical tools to maximize user engagement and research utility.
Database expansion improves accessibility and utility of transcription factor binding profiles
The 9th release of JASPAR significantly expands its collection of transcription factor binding profiles and introduces new tools and access methods, enhancing its utility for researchers.
Nucleic Acids Research · 2021
Key Findings
- 01JASPAR CORE collection expanded by 341 new profiles (19% increase)
- 02298 new profiles added to the Unvalidated collection
- 03Familial binding profiles provided through clustering for each taxonomic group
- 04Structural classification of DNA binding domains revised for plant-specific TFs
- 05Word clouds introduced for representing scientific knowledge per TF
Application
Design takeaway
For complex data platforms, continuously expand content, offer multiple access points, and embed analytical tools to maximize user engagement and research utility.
How to apply
When designing a data-heavy platform, plan for iterative content expansion and provide both graphical user interfaces and programmatic interfaces (APIs, SDKs) to serve a broad user base. Include built-in tools for common data analysis tasks.
Project actions
- 01When designing a data-heavy system, think about how users will access the data (website, code, etc.) and offer multiple options.
- 02Always plan to add more content over time to keep your database useful and up-to-date.
- 03Consider adding tools directly into your system that help users analyze the data, not just view it.
Method & Evidence
Variables
Strengths & Limitations
Strengths
- +Comprehensive expansion of a critical scientific resource
- +Introduction of multiple new features and access methods
- +Commitment to open-access and manual curation
Limitations
This is a technical paper about database development, not a user study. Therefore, direct evidence of improved user experience is not presented, only implied by the added features.
Reliability & validity
The reliability of the database content is enhanced by manual curation and clustering. The validity of the new tools and access methods in improving user workflow would need to be assessed through user studies, which are not part of this paper.
Think critically
How might the design of the new Python package (pyJASPAR) influence the adoption rate among computational biologists compared to the web interface for experimental biologists?
Design Principles
"Comprehensive Accessibility & Integrated Utility"
Researchers rely on comprehensive and accessible databases for genomic analysis. Expanding data coverage and providing diverse access points reduces friction in data retrieval and analysis, allowing scientists to focus more on discovery and less on data wrangling. This directly impacts the efficiency and breadth of biological research.
What This Means for Your Design
This paper shows that making a science database bigger and easier to use, with new ways to look at and get the data, helps scientists do their work better.
How to use in your project
- 1.Reference the multi-modal access (web, API, Python package) as an example of robust information architecture for diverse user needs.
- 2.Discuss the clustering of profiles and revised classifications as strategies for organizing large, complex datasets.
Add to My Project
Quick Cite
Paragraph starter
The JASPAR 2022 release demonstrates that expanding content, offering diverse access methods (web, API, Python package), and integrating analytical tools significantly enhances the utility and accessibility of complex scientific databases (Castro-Mondragón et al., 2021).
Source
Nucleic Acids Research
JASPAR 2022: the 9th release of the open-access database of transcription factor binding profiles
journal · 2021
View sourceQuestions About This Research
- What does the research say about database expansion improves accessibility and utility of transcription factor binding profiles?
- For complex data platforms, continuously expand content, offer multiple access points, and embed analytical tools to maximize user engagement and research utility. Evidence: Nucleic Acids Research (2021).
- Why does "Database expansion improves accessibility and utility of transcription factor binding profiles" matter for design?
- Researchers rely on comprehensive and accessible databases for genomic analysis. Expanding data coverage and providing diverse access points reduces friction in data retrieval and analysis, allowing scientists to focus more on discovery and less on data wrangling. This directly impacts the efficiency and breadth of biological research.
- How can designers apply this research?
- For complex data platforms, continuously expand content, offer multiple access points, and embed analytical tools to maximize user engagement and research utility.
- What were the main findings?
- JASPAR CORE collection expanded by 341 new profiles (19% increase). 298 new profiles added to the Unvalidated collection. Familial binding profiles provided through clustering for each taxonomic group. Structural classification of DNA binding domains revised for plant-specific TFs
- What research method was used?
- Database expansion and feature development.
- How strong is the evidence?
- Evidence strength is rated Strong effect, based on a 2021 journal from Nucleic Acids Research.
- What should I do differently in my next project?
- When designing a data-heavy platform, plan for iterative content expansion and provide both graphical user interfaces and programmatic interfaces (APIs, SDKs) to serve a broad user base. Include built-in tools for common data analysis tasks.
- What are the limitations?
- The paper describes database updates rather than a user study, so direct user experience improvements are inferred rather than measured. The quality of the 'Unvalidated' collection relies on future orthogonal evidence.