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Related Experiment Videos

DbW: automatic update of a functional family-specific multiple alignment.

V Prigent1, J C Thierry, O Poch

  • 1Laboratoire de Biologie et Génomique Structurales, Institut de Génétique et de Biologie Moléculaire et Cellulaire, (CNRS/INSERM/ULP) BP 10142, 67404 Illkirch, Cedex, France. prigent@igbmc.u-strasbg.fr

Bioinformatics (Oxford, England)
|December 16, 2004
PubMed
Summary

DbW is a new program that automates updating multiple sequence alignments for protein families. It accurately identifies homologous sequences, aiding in functional analysis and structure prediction.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Exponential growth of sequence data necessitates automated analysis tools.
  • Functional family-specific multiple alignments are crucial for biological insights.
  • Existing methods may struggle with the scale and complexity of modern sequence databases.

Purpose of the Study:

  • To introduce DbW, a novel program for automating the update of functional family-specific multiple sequence alignments.
  • To enhance the inclusion of relevant homologous sequences in alignments.
  • To leverage diverse data sources, including sequence and annotation information.

Main Methods:

  • Development of the DbW software program.
  • Utilizing sequence and annotation data from biological databases.

Related Experiment Videos

  • Testing and validation using aminoacyl-tRNA synthetase families.

    • Main Results:

    • DbW effectively detects homologous sequences in Swiss-Prot and SPTREMBL databases.
    • Achieved high global specificity (98.4%) and sensitivity (95.2%) in identifying family-specific sequences.
    • Demonstrated the program's utility for aminoacyl-tRNA synthetase families.

    Conclusions:

    • DbW offers a reliable method for generating accurate multiple sequence alignments.
    • The software facilitates downstream applications such as functional residue identification and structure prediction.
    • DbW addresses the challenge of managing and analyzing rapidly expanding genomic datasets.