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

Modeling amino acid replacement.

T Müller1, M Vingron

  • 1Deutsches Krebsforschungszentrum, Theoretische Bioinformatik, 69120 Heidelberg, Germany. t.mueller/m.vingron

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|May 31, 2001
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

Stochastics of Cellular Differentiation Explained by Epigenetics: The Case of T-Cell Differentiation and Functional Plasticity.

Scandinavian journal of immunology·2017
Same author

X-exome sequencing of 405 unresolved families identifies seven novel intellectual disability genes.

Molecular psychiatry·2015
Same author

Developments in CORG: a gene-centric comparative genomics resource.

Nucleic acids research·2006
Same author

Mathematical tree models for cytogenetic development in solid tumors.

Verhandlungen der Deutschen Gesellschaft fur Pathologie·2006
Same author

SVC: structured visualization of evolutionary sequence conservation.

Nucleic acids research·2005
Same author

Genome wide identification and classification of alternative splicing based on EST data.

Bioinformatics (Oxford, England)·2004
Same journal

GMSA: A Graph Matching and Point Cloud Registration-Based Method for Spatial Transcriptomics Data Alignment.

Journal of computational biology : a journal of computational molecular cell biology·2026
Same journal

Investigations on Multiple Protein Scaffold Filling.

Journal of computational biology : a journal of computational molecular cell biology·2026
Same journal

Cell Type Prediction for Single-Cell RNA Sequencing Utilizing Unsupervised Domain Adaptation and Semi-Supervised Learning.

Journal of computational biology : a journal of computational molecular cell biology·2026
Same journal

PPIGAN: Prediction of Protein-Protein Interactions Using Generative Adversarial Networks.

Journal of computational biology : a journal of computational molecular cell biology·2026
Same journal

Deep Structure-Enhanced Cell Clustering Model for Single-Cell RNA Sequencing Data.

Journal of computational biology : a journal of computational molecular cell biology·2026
Same journal

Asymmetric Drug-Drug Interaction Prediction Based on Generative Adversarial Networks and Knowledge Graph.

Journal of computational biology : a journal of computational molecular cell biology·2026
See all related articles

This study introduces a new resolvent method to estimate amino acid replacement frequencies, improving upon Dayhoff

Area of Science:

  • Molecular Evolution
  • Bioinformatics
  • Computational Biology

Background:

  • Amino acid replacement frequencies are vital for sequence analysis, database searching, and phylogenetic analysis.
  • Dayhoff et al. developed PAM score matrices using a Markov model, but their method is limited to proteins with small divergence.
  • Accurate models of protein evolution are essential for understanding biological sequences.

Purpose of the Study:

  • To present an improved estimator, the resolvent method, for amino acid substitution models.
  • To overcome the limitations of previous methods regarding the degree of protein divergence.
  • To enable estimation of amino acid substitution models from alignments with varying divergence.

Main Methods:

  • Development of the resolvent method, an extension of Dayhoff's approach.

Related Experiment Videos

  • Estimation of amino acid substitution models using alignments of varying divergence.
  • Extensive simulations to validate the accuracy of the new estimator.

    • Main Results:

    • The resolvent method accurately recovers exchange frequencies among amino acids.
    • The new method is not restricted by the degree of protein divergence.
    • Recomputation of score matrices using the SYSTERS database.

    Conclusions:

    • The resolvent method offers a more versatile and accurate approach to modeling protein evolution.
    • This advancement facilitates more robust sequence analysis and phylogenetic studies.
    • The recomputed score matrices provide improved tools for bioinformatics applications.