Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Genome structure described by formal languages.

V Brendel, H G Busse

    Nucleic Acids Research
    |March 12, 1984
    PubMed
    Summary
    This summary is machine-generated.

    Formal languages and finite automata can describe the grammatical patterns in genetic information, offering a concise way to analyze DNA and RNA sequences. This method provides a novel framework for understanding biological sequence structures.

    Related Concept Videos

    You might also read

    Related Articles

    Articles linked to this work by shared authors, journal, and citation graph.

    Sort by
    Same author

    Spliceosomal proteins in plants.

    Current topics in microbiology and immunology·2008
    Same author

    Sustained oscillations in glycolysis: an experimental and theoretical study of chaotic and complex periodic behavior and of quenching of simple oscillations.

    Biophysical chemistry·2006
    Same author

    Multi-query sequence BLAST output examination with MuSeqBox.

    Bioinformatics (Oxford, England)·2001
    Same author

    Optimal spliced alignment of homologous cDNA to a genomic DNA template.

    Bioinformatics (Oxford, England)·2000
    Same author

    Gene structure prediction by spliced alignment of genomic DNA with protein sequences: increased accuracy by differential splice site scoring.

    Journal of molecular biology·2000
    Same author

    Test of the combinatorial model of intron recognition in a native maize gene.

    Plant molecular biology·2000
    Same journal

    Correction to 'New origin firing is inhibited by APC/CCdh1 activation in S-phase after severe replication stress'.

    Nucleic acids research·2026
    Same journal

    VeloRM: disentangling pre- and post-splicing RNA modification dynamics at single-cell resolution.

    Nucleic acids research·2026
    Same journal

    Accessibility of telomeric overhangs to stabilizing small-molecule ligands.

    Nucleic acids research·2026
    Same journal

    Multivalent interactions mediate SNAIL transcription factor stimulation of the nucleosome deacetylase activity of the CoREST complex.

    Nucleic acids research·2026
    Same journal

    Genome-wide mapping of DNA G-quadruplexes in Trypanosoma brucei chromatin reveals enrichment in coding regions and transcription start sites.

    Nucleic acids research·2026
    Same journal

    Correction to 'The Gene Ontology knowledgebase in 2026'.

    Nucleic acids research·2026
    See all related articles

    Area of Science:

    • Bioinformatics and Computational Biology
    • Molecular Biology
    • Formal Language Theory

    Background:

    • Nucleic acid sequences (DNA and RNA) can be viewed as words formed from a nucleotide alphabet.
    • Naturally occurring sequences represent specific subsets within the universe of all possible sequences.
    • Understanding the structural patterns within these subsets is crucial for deciphering genetic information.

    Purpose of the Study:

    • To propose the application of formal language theory for describing the structure of naturally occurring nucleic acid sequences.
    • To demonstrate how regular languages and finite automata can characterize grammatical patterns in genetic information.
    • To provide a concise method for analyzing sequence subsets, exemplified by Group I RNA phages.

    Main Methods:

    Related Experiment Videos

  • Conceptualizing nucleic acid sequences as words over a nucleotide alphabet.
  • Applying formal language theory, specifically regular languages, to model sequence structures.
  • Utilizing finite automata to define and recognize these regular languages.
  • Demonstrating the application with an analysis of Group I RNA phage sequences.

    • Main Results:

    • Formal languages provide a framework for concisely characterizing grammatical patterns in nucleic acid sequences.
    • Regular languages and finite automata effectively model subsets of naturally occurring DNA and RNA sequences.
    • The approach successfully applied to Group I RNA phages, demonstrating its practical utility.

    Conclusions:

    • Formal language theory offers a powerful and concise method for analyzing the structure of genetic information.
    • This approach enables a systematic characterization of biological sequence grammars.
    • The use of finite automata provides a computational tool for studying sequence patterns in molecular biology.