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Deafness mutation mining using regular expression based pattern matching.

Christopher M Frenz1

  • 1Department of Computer Engineering Technology, New York City College of Technology (CUNY), 300 Jay St, Brooklyn, NY 11201, USA. cfrenz@gmail.com

BMC Medical Informatics and Decision Making
|October 27, 2007
PubMed
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This study introduces a Perl utility for enhanced PubMed searches using regular expressions, improving data accuracy. The tool was used to identify all DFN deafness mutations in human ear records.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomic Databases

Background:

  • Keyword-based database searches (e.g., PubMed) are useful but have limitations.
  • Regular expressions offer enhanced pattern matching beyond single keywords.
  • Distinguishing similar character sequences and identifying complex element types is challenging with keywords alone.

Purpose of the Study:

  • To develop a utility for integrating regular expression searches into PubMed.
  • To improve the accuracy and comprehensiveness of database retrieval.

Main Methods:

  • Development of a Perl-based software utility.
  • Implementation of regular expression querying capabilities for PubMed.
  • Application of the utility to a specific genetic research query.

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Main Results:

  • A functional Perl utility enabling regular expression searches in PubMed was created.
  • The utility demonstrated improved search accuracy compared to traditional keyword methods.
  • Successful identification of DFN deafness mutations within relevant PubMed records.

Conclusions:

  • Regular expressions significantly enhance the precision of biological database searches.
  • The developed utility provides a powerful tool for researchers, exemplified by its application in identifying deafness mutations.
  • This approach facilitates more comprehensive data mining in biomedical literature.