dbMisLoc: A Manually Curated Database of Conditional Protein Mis-localization Events

Over the last few years, an increasing number of protein mis-localization events have been reported under various conditions. It is important to understand these events and their relationship with complex disorders. Although many efforts had been made in establishing models with statistical or machi...

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Bibliographic Details
Published in:Interdisciplinary sciences : computational life sciences 2023-09, Vol.15 (3), p.433-438
Main Authors: Wang, Ren-Hua, Luo, Tao, Guo, Yu-Peng, Yang, Zi-Xin, Zhang, He-Yi, Hao, Hong-Yu, Du, Pu-Feng
Format: Article
Language:English
Subjects:
Algorithms
Biomedical and Life Sciences
Computational Biology/Bioinformatics
Computational Science and Engineering
Computer Appl. in Life Sciences
Health Sciences
Life Sciences
Localization
Machine learning
Mathematical and Computational Physics
Mathematical models
Medicine
Original Research Article
Proteins
Search engines
Source code
Statistical analysis
Statistics for Life Sciences
Theoretical
Theoretical and Computational Chemistry
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Summary:Over the last few years, an increasing number of protein mis-localization events have been reported under various conditions. It is important to understand these events and their relationship with complex disorders. Although many efforts had been made in establishing models with statistical or machine learning algorithms, a comprehensive database resource is still missing. Since the records of experimental-validated protein mis-localization events spread across many literatures, a collection of all these reports in a unique website is demanded. In this paper, we created the dbMisLoc database by manually curating conditional protein mis-localization events from various literatures. The dbMisLoc database records the protein localizations, mis-localizations, conditions for mis-localization, and the original reports. The dbMisLoc database allows the users to intuitively view, search, visualize and download protein mis-localization records. The dbMisLoc database integrates a BLAST search engine, which can search mis-localized proteins that are similar to user queries. The dbMisLoc database can be accessed directly through ( https://dbml.pufengdu.org ). The source code of dbMisLoc database is available from the GitHub repository ( https://github.com/quinlanW/dbMisLoc ) for free. Users can host their own mirrors of dbMisLoc database on their own servers. Graphical Abstract dbMisLoc is database for manually curated protein mis-localization events. It contains mis-localization events in 14 categories of conditions such as diseases, drug treatments and environmental stresses.
ISSN:1913-2751
1867-1462
DOI:10.1007/s12539-023-00564-0