MSGD: a manually curated database of genomic, transcriptomic, proteomic and drug information for multiple sclerosis

Area of Science:

• Neuroscience
• Genetics
• Bioinformatics

Background:

• Multiple sclerosis (MS) is a prevalent inflammatory demyelinating disease of the central nervous system.
• 'Omics' data (genomics, transcriptomics, proteomics) are crucial for understanding MS but are fragmented across literature.
• Existing data accessibility challenges hinder comprehensive analysis and utilization for MS research.

Purpose of the Study:

• To develop a centralized, curated database for 'omics' and drug information related to multiple sclerosis.
• To provide a user-friendly platform for researchers to access, analyze, and contribute MS-related genetic and molecular data.
• To facilitate the deciphering of gene mechanisms and improve MS prevention, diagnosis, and treatment.

Main Methods:

• Manual mining and compilation of data from 5485 scientific publications.
• Construction of the Multiple Sclerosis Gene Database (MSGD) with detailed entries.
• Development of a user-friendly web interface for data searching, viewing, and submission.

Main Results:

• The MSGD currently contains 6255 entries, including variants, RNA, protein, knockout, drug, and high-throughput data.
• Each entry provides comprehensive details such as species, disease type, gene descriptions, and references.
• The database offers functionalities for gene searching, expression pattern viewing, gene set management, and new association submissions.

Conclusions:

• The MSGD serves as a valuable, accessible resource for multiple sclerosis research.
• By consolidating scattered data, MSGD aims to lower barriers to data interpretation and utilization.
• This initiative is expected to significantly advance research into MS pathogenesis and therapeutic strategies.