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SEQSEE: a comprehensive program suite for protein sequence analysis

D S Wishart1, R F Boyko, L Willard

  • 1Department of Biochemistry, University of Alberta, Edmonton, Canada.

Computer Applications in the Biosciences : CABIOS
|April 1, 1994
PubMed
Summary
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SEQSEE (SEQuence SEEker) is a free, integrated software suite for protein sequence and database analysis. It offers advanced features like alignment, pattern matching, and secondary structure prediction, enhancing research capabilities.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Molecular Biology

Background:

  • Protein sequence analysis is crucial for understanding biological functions.
  • Existing software packages often lack comprehensive integration or are proprietary.
  • There is a need for accessible, versatile tools for protein sequence data management and analysis.

Purpose of the Study:

  • To introduce SEQSEE (SEQuence SEEker), a comprehensive software suite for protein sequence and database analysis.
  • To provide an integrated, state-of-the-art package for diverse analytical tasks.
  • To offer a freely available alternative to commercial software.

Main Methods:

  • Development of a multi-purpose, menu-driven suite of programs.
  • Integration of standard and unique databases for specialized analyses.

Related Experiment Videos

  • Enhancement of existing algorithms for improved performance.
  • Configuration for UNIX-based systems with potential for other architectures.

    • Main Results:

    • SEQSEE performs a wide range of analytical tasks including sequence/database searching, alignment, pattern matching, and secondary structure prediction.
    • Unique databases enable structure-based and homology-based sequence analyses.
    • Enhanced algorithms lead to superior performance compared to many commercial products.
    • The software is designed for broad compatibility across different UNIX workstations.

    Conclusions:

    • SEQSEE provides a powerful, integrated, and freely accessible platform for protein sequence analysis.
    • Its comprehensive features and enhanced algorithms support advanced research in bioinformatics and molecular biology.
    • The availability of source code, documentation, and databases promotes wider adoption and research collaboration.