LCRAnnotationsDB: A Database for Low Complexity Regions in Proteins
Author Information
Author(s): Ziemska-Legiecka Joanna, Jarnot Patryk, Szymańska Sylwia, Błaszczyk Dagmara, Staśczak Alicja, Langer-Macioł Hanna, Lucińska Kinga, Widzisz Karolina, Janas Aleksandra, Słowik Hanna, Śliwińska Wiktoria, Gruca Aleksandra, Grynberg Marcin
Primary Institution: Institute of Biochemistry and Biophysics, Polish Academy of Sciences, Warsaw, Poland
Hypothesis
LCRAnnotationsDB aims to consolidate knowledge about low complexity regions (LCRs) and store relevant annotations in a single place.
Conclusion
LCRAnnotationsDB provides a comprehensive resource for functional analysis of low complexity regions in proteins, integrating data from multiple sources.
Supporting Evidence
- LCRAnnotationsDB integrates annotations from multiple databases, making it a unique resource.
- The database allows for the functional analysis of low complexity regions in proteins.
- More than half of the LCR annotations are significantly enriched within InterPro Families.
- The study highlights the importance of low complexity regions in protein function.
- Users can automate analyses and download data using a RESTful API.
- The database categorizes annotations to resolve duplicative information across sources.
- Manual curation of LCRs is planned to enhance the database's content.
- The database provides a user-friendly interface for searching and browsing LCR information.
Takeaway
This study created a database to help scientists find and understand important parts of proteins that are made up of simple building blocks.
Methodology
The database was constructed using the SEG method to identify low complexity regions in protein sequences, integrating annotations from various public databases.
Potential Biases
There is a potential bias due to the reliance on specific databases that may not represent all proteins equally.
Limitations
The database may not cover all possible low complexity regions and relies on existing annotations which may be incomplete.
Statistical Information
P-Value
p<0.05
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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