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

Deriving an amino acid distance matrix

W R Taylor1, D T Jones

  • 1Laboratory of Mathematical Biology, National Institute for Medical Research, Ridgeway, London, U.K.

Journal of Theoretical Biology
|September 7, 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

Publisher Correction: Brain charts for the human lifespan.

Nature·2022
Same author

Brain charts for the human lifespan.

Nature·2022
Same author

Can tibio-femoral kinematic and kinetic parameters reveal poor functionality and underlying deficits after total knee replacement? A systematic review.

The Knee·2021
Same author

Changes in Ventricular and Cortical Volumes following Shunt Placement in Patients with Idiopathic Normal Pressure Hydrocephalus.

AJNR. American journal of neuroradiology·2021
Same author

In Vivo Elongation Patterns of the Collateral Ligaments in Healthy Knees During Functional Activities.

The Journal of bone and joint surgery. American volume·2021
Same author

Length-Change Patterns of the Collateral Ligaments During Functional Activities After Total Knee Arthroplasty.

Annals of biomedical engineering·2020

Researchers explored converting amino acid similarity data into distance matrices. Simple negation and inter-row distance methods showed promise for applications in sequence alignment and phylogenetic tree construction.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Biophysics

Background:

  • Amino acid similarity matrices are fundamental in biological sequence analysis.
  • Converting these matrices into low-dimensional, metric distance matrices is crucial for various downstream applications.
  • Existing methods may lack efficiency or accuracy in representing complex relationships.

Purpose of the Study:

  • To investigate diverse methods for transforming amino acid similarity matrices into low-dimensional, metric distance matrices.
  • To evaluate the effectiveness of different transformation techniques, including projection and inversion methods.
  • To identify optimal approaches for preserving essential data characteristics in the transformed matrices.

Main Methods:

  • Exploration of projection techniques for matrix transformation.

Related Experiment Videos

  • Investigation of various inversion forms, including simple negation normalized by diagonal elements.
  • Application of inter-row distance calculations.
  • Utilizing weighted least-squares minimization for evaluation.
  • Derivation of a rank-ordered matrix form with 3D spatial constraints.

    • Main Results:

    • No single unique transformation was identified using projection techniques.
    • Simple negation normalized by diagonal elements provided a good fit to the original data.
    • Inter-row distance yielded a comparable fit and was preferred via weighted least-squares minimization.
    • A rank-ordered form created a network configuration similar to previous analyses of amino acid physicochemical properties.

    Conclusions:

    • The developed distance matrix forms are suitable for sequence alignment and pattern-matching algorithms.
    • These methods can be applied to the construction of phylogenetic trees.
    • The findings offer novel approaches for representing amino acid relationships in computational biology.