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

Some useful statistical properties of position-weight matrices

J M Claverie1

  • 1National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894.

Computers & Chemistry
|September 1, 1994
PubMed
Summary

This study introduces a statistically robust method for assessing the significance of sequence motif matches using position-weight matrices. This enables sensitive scanning of protein databases for biologically significant patterns.

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

Global warming and planetary health: An open letter to the WHO from scientific and indigenous people urging for paleo-microbiology studies.

Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases·2020
Same author

Distribution patterns of microbial communities in ultramafic landscape: a metagenetic approach highlights the strong relationships between diversity and environmental traits.

Molecular ecology·2016
Same author

T cells recognize antigen alone and not MHC molecules.

Immunology today·2014
Same author

Mimivirus.

Current topics in microbiology and immunology·2009
Same author

Rickettsia felis, from culture to genome sequencing.

Annals of the New York Academy of Sciences·2006
Same author

Recent advances in computational genomics.

Pharmacogenomics·2001

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Sequence Analysis

Background:

  • Position-weight matrices (PWMs) are used for identifying sequence motifs but lack reliable statistical significance assessment.
  • This limitation hinders their application in large-scale database searches.

Purpose of the Study:

  • To develop a statistically sound method for evaluating PWM matching scores.
  • To enable sensitive and reliable detection of biological sequence patterns.

Main Methods:

  • Reviewed three computation schemes for designing PWMs from sequence alignments.
  • Demonstrated that scores for patterns >= 10 positions follow an extreme value (Gumbel) distribution.
  • Utilized the Gumbel distribution to establish a statistical significance threshold.

Related Experiment Videos

Main Results:

  • The Gumbel distribution accurately models scores from random sequence matches.
  • The derived threshold effectively distinguishes true positive matches from random occurrences.
  • Enables sensitive scanning of entire protein databases for sequence motifs.

Conclusions:

  • The developed statistical method overcomes limitations in PWM usage.
  • Allows for highly sensitive and statistically validated motif discovery in biological sequences.
  • The MODEST software suite implements these improvements for practical application.