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

Consensus functions and patterns in molecular sequences

B Mirkin1, F S Roberts

  • 1Department of Informatics and Applied Statistics, Central Economics- Mathematics Institute, Moscow, Russia.

Bulletin of Mathematical Biology
|January 1, 1993
PubMed
Summary
This summary is machine-generated.

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

Comparative genomics of the lactic acid bacteria.

Proceedings of the National Academy of Sciences of the United States of America·2006
Same author

Duplication-based measures of difference between gene and species trees.

Journal of computational biology : a journal of computational molecular cell biology·1998
Same author

AIDS clinical trials: why they have recruiting problems.

AIDS treatment news·1995
Same author

A biologically consistent model for comparing molecular phylogenies.

Journal of computational biology : a journal of computational molecular cell biology·1995
Same author

Report of the task force on blood pressure control in children.

Pediatrics·1977
Same journal

Effects of Seasonal Births and Predation on Disease Spread.

Bulletin of mathematical biology·2026
Same journal

Identifiability, Sensitivity, and Genetic Algorithms in Bacterial Biofilm Selection Models.

Bulletin of mathematical biology·2026
Same journal

Slow Evolution Towards Generalism in a Model of Variable Dietary Range.

Bulletin of mathematical biology·2026
Same journal

CBINN: Cancer Biology-Informed Neural Network for Unknown Parameter Estimation and Missing Physics Identification.

Bulletin of mathematical biology·2026
Same journal

A Cost-Sensitive Behavioral Modeling Analysis of the Early Identification and Control of Infectious Diseases.

Bulletin of mathematical biology·2026
Same journal

Tracking Dynamics of Superspreading Through Contacts, Exposures, and Transmissions in Edge-Based Network Epidemics.

Bulletin of mathematical biology·2026
See all related articles

This study explores consensus methods from social sciences applied to molecular biology. It reveals how common methods like the median and mean are specific instances of a broader consensus technique, enhancing pattern recognition in molecular sequences.

Area of Science:

  • Molecular Biology
  • Bioinformatics
  • Computational Biology

Background:

  • Consensus methods, originating in social sciences, are increasingly adopted in molecular biology for sequence analysis.
  • Identifying patterns in molecular sequences, especially those with positional variability, is crucial for biological research.

Purpose of the Study:

  • To analyze a specific consensus method developed by Waterman et al. for molecular sequence pattern identification.
  • To demonstrate the relationship between social science consensus methods (median, mean) and the Waterman et al. method.
  • To clarify parameter choices that link these different consensus approaches.

Main Methods:

  • Investigated the consensus method by Waterman et al. for identifying variable patterns within molecular sequences.

Related Experiment Videos

  • Analyzed specific parameter settings within the Waterman et al. method.
  • Compared the Waterman et al. method with established social science consensus procedures.

    • Main Results:

    • Showed that the median and mean consensus methods are special cases of the Waterman et al. method under specific parameter configurations.
    • Provided a detailed explanation of the parameters that define these special cases.
    • Demonstrated the equivalence of the Waterman et al. method, with its specific parameters, to the widely used social science 'median procedure'.

    Conclusions:

    • The study bridges consensus methodologies between social sciences and molecular biology.
    • Understanding these connections allows for more robust pattern recognition in molecular sequence data.
    • This work facilitates the application of established social science techniques to complex biological sequence analysis problems.