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BIOSPIDA: A Relational Database Translator for NCBI.

Matthew S Hagen1, Eva K Lee

  • 1Center for Operations Research in Medicine and HealthCare.

AMIA ... Annual Symposium Proceedings. AMIA Symposium
|February 25, 2011
PubMed
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Scientists face challenges accessing integrated biological data. This study introduces a universal parser and translator to link NCBI databases, simplifying data retrieval for biological entities.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Database Management

Background:

  • Biological databases are rapidly expanding, making it difficult for researchers to find comprehensive information on biological entities.
  • Data on nucleotide sequences, gene expression, molecular interactions, and 3D structures are dispersed across numerous databases.

Purpose of the Study:

  • To develop an integrated system for querying multiple biological databases efficiently.
  • To introduce tools for parsing and translating National Center for Biotechnology Information (NCBI) databases for easier integration.

Main Methods:

  • A universal parser and relational schema translator were developed for Abstract Syntax Notation (ASN.1) data models.
  • Data models from OMIM, Entrez-Gene, Pubmed, MMDB, and GenBank were converted into relational databases.

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Main Results:

  • Successfully converted multiple NCBI database data models into a unified relational format.
  • Demonstrated that these converted databases are easily linkable, facilitating complex biological queries.
  • The developed tools enable local integration of NCBI databases with reduced workload and development time.

Conclusions:

  • The introduced tools significantly simplify the process of integrating and querying diverse biological databases.
  • Researchers can now access and analyze integrated biological information more effectively, accelerating scientific discovery.