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Related Experiment Videos

Matching relational patterns in nucleic acid sequences.

W Saurin1, P Marlière

  • 1Unité de Programmation Moléculaire et Toxicologie Génétique, CNRS UA271, INSERM U163, Paris, France.

Computer Applications in the Biosciences : CABIOS
|June 1, 1987
PubMed
Summary

This study introduces a novel program for efficiently searching sequence databases using complex relational patterns. The algorithm offers flexibility, allowing for easy expansion of searchable relations without core program modification.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Algorithm Development

Background:

  • Efficient searching of large sequence data banks is crucial for biological research.
  • Existing pattern matching algorithms may lack flexibility for complex, relation-based queries.

Purpose of the Study:

  • To present a new program designed for efficient searching of sequence data banks.
  • To enable the identification of complex patterns linked by various relations (e.g., identity, complementarity, span).

Main Methods:

  • Development of a program utilizing an algorithm distinct from traditional finite state machines.
  • The algorithm is inspired by principles of automatic demonstration.
  • The program is implemented in Pascal-ISO and designed for microcomputer execution.

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Main Results:

  • The program efficiently searches sequence data banks for complex patterns.
  • The algorithm allows for the enrichment of the repertory of relations without altering the core program.
  • Demonstrates a flexible approach to pattern searching in biological sequences.

Conclusions:

  • The developed program offers an efficient and flexible method for complex pattern searching in sequence data.
  • The approach provides a foundation for adaptable sequence analysis tools.
  • Highlights the potential of non-finite state machine algorithms in bioinformatics.