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On-line tools for sequence retrieval and multivariate statistics in molecular biology
1Laboratoire de Biométrie, Génétique et Biologie des Populations, URA CNRS No.2055, Université Claude Bernard-Lyon, Villeurbanne, France.
Computer Applications in the Biosciences : CABIOS
|February 1, 1996
Summary
A new web server enables browsing and multivariate analysis of biological sequence data. This tool aids in identifying gene function and understanding evolutionary relationships within sequence collections.
Area of Science:
- Bioinformatics
- Computational Biology
- Genomics
Background:
- Accessing and analyzing large biological sequence datasets is crucial for understanding gene function and evolutionary relationships.
- Existing tools often lack integrated capabilities for both browsing diverse sequence collections and performing advanced statistical analyses.
Purpose of the Study:
- To develop a World-Wide Web server for browsing sequence collections (ACNUC format) and performing multivariate analyses.
- To provide access to general (GenBank, EMBL) and specialized (Hovergen, NRSub) biological databases.
- To enable complex query construction and subsequent analysis of retrieved sequence lists.
Main Methods:
- Development of a web server integrating sequence browsing and multivariate analysis functionalities.
- Implementation of complex query construction for sequence retrieval.
- Application of multivariate statistical methods, including correspondence analysis and principal coordinate analysis, on sequence data.
Main Results:
- Demonstrated application in analyzing codon usage of Haemophilus influenzae Rd protein genes, identifying highly expressed and integral membrane proteins.
- Successfully re-established patterns of relationships among 70 aligned growth hormone protein sequences using principal coordinate analysis, corroborating tree-building program results.
Conclusions:
- The developed web server provides a powerful platform for integrated sequence data browsing and multivariate analysis.
- This approach facilitates the identification of functional gene properties and the elucidation of evolutionary patterns within biological sequence collections.