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Southern Blot02:57

Southern Blot

Agarose gel electrophoresis is very useful in separating DNA fragments by size. Running a DNA ladder containing fragments of the known length alongside the sample helps determine the approximate length of the sample DNA fragments. However, additional steps are needed to verify the sequence identity of the sample DNA fragments.
Denatured DNA fragments must be transferred onto a carrier membrane from the gel to make it accessible to a probe - a small ssDNA fragment complementary to the target DNA...

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RegExpBlasting (REB), a Regular Expression Blasting algorithm based on multiply aligned sequences.

Francesco Rubino1, Marcella Attimonelli

  • 1Department of Biochemistry and Molecular Biology E, Quagliariello - Bari, 70126, Italy. rubino.francesco@gmail.com

BMC Bioinformatics
|June 19, 2009
PubMed
Summary

The RegExpBlasting (REB) algorithm enables functional characterization of new nucleotide sequences by comparing them against patterns derived from MultiAlignments. This bioinformatics tool enhances sequence analysis and database management, demonstrating powerful flexibility.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Bioinformatics tools like Blast and FASTA are commonly used for functional characterization of nucleotide sequences.
  • Comparing sequences against MultiAlignments (MA) presents unique challenges not fully addressed by existing methods.
  • The RegExpBlasting (REB) algorithm is introduced to address the need for comparing sequences against pattern datasets derived from MAs.

Purpose of the Study:

  • To present the RegExpBlasting (REB) algorithm for functional characterization of unclassified nucleotide sequences.
  • To demonstrate the application of REB in the PPNEMA resource for classifying nematode rDNA sequences and updating the database.
  • To highlight the flexibility and power of REB in bioinformatics sequence analysis.

Main Methods:

  • The REB algorithm defines a dataset of multialignments (MAs).
  • Each MA is associated with a pattern generated using regular expression rules.
  • Submitted biosequences are automatically characterized based on the best-matching pattern.

Main Results:

  • The REB algorithm is implemented in the PPNEMA resource's "characterize your sequence" tool.
  • PPNEMA utilizes REB for classifying new nematode rDNA sequences and retrieving plant nematode multialigned sequences.
  • REB facilitates automatic updating of the PPNEMA database, showcasing its practical application.

Conclusions:

  • The application of REB within PPNEMA demonstrates its effectiveness for database updating and sequence characterization.
  • REB offers a rapid solution for bioinformatics problems requiring the addition of new sequences to pre-existing clusters.
  • Statistical tests confirm the method's powerful flexibility and broad applicability in bioinformatics.