The translational signal database, TransTerm, is now a relational database

Area of Science:

• * Molecular Biology
• * Bioinformatics
• * Genomics

Background:

• * Understanding gene expression regulation is crucial for deciphering cellular mechanisms.
• * Codon usage and sequence contexts play a significant role in translational efficiency and control.
• * Existing databases may lack comprehensive data on initiation and termination contexts across diverse species.

Purpose of the Study:

• * To compile and present a large, non-redundant collection of coding sequence initiation and termination contexts.
• * To provide valuable coding sequence parameters such as Nc, GC3, and codon adaptation index (CAI).
• * To facilitate research in translational control by creating an accessible relational database.

Main Methods:

• * Compiled over 97,500 non-redundant coding sequence contexts from GenBank release 101.
• * Incorporated data for over 325 species and organelles, including complete bacterial and eukaryotic genomes.
• * Developed a relational database using PostgreSQL with SQL access and a World Wide Web interface.

Main Results:

• * TransTerm-97 offers extensive data on start and stop codon contexts and codon usage tables.
• * The database includes coding sequence parameters like length, Nc, GC3, and CAI.
• * Data spans a wide range of organisms, supporting comparative genomics and evolutionary studies.

Conclusions:

• * TransTerm-97 serves as a valuable resource for studying translational control and codon usage.
• * The relational database structure and web interface enhance accessibility for researchers.
• * Future extensions aim to include untranslated regions (UTRs) for even more comprehensive analysis.