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

Correlations in protein sequences and property codes

O Weiss1, H Herzel

  • 1Institute for Theoretical Biology, Humboldt University Berlin, Invalidenstr. 43, Berlin, D-10115, Germany.

Journal of Theoretical Biology
|June 6, 1998
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

Outcomes and rate of return to play in elite athletes following arthroscopic surgery of the hip.

International orthopaedics·2021
Same author

Keeping children safe: a model for predicting families at risk for recurrent childhood injuries.

Public health·2019
Same author

Influence of wood ash pre-treatment on leaching behaviour, liming and fertilising potential.

Waste management (New York, N.Y.)·2018
Same author

Anti-phosphorylated histone H2AThr120: a universal microscopic marker for centromeric chromatin of mono- and holocentric plant species.

Cytogenetic and genome research·2014
Same author

Genetic redundancy strengthens the circadian clock leading to a narrow entrainment range.

Journal of the Royal Society, Interface·2013
Same author

Mathematical modeling in chronobiology.

Handbook of experimental pharmacology·2013
Same journal

The male-biased sex ratio in humans and its role in the transition from promiscuity to pair bonding.

Journal of theoretical biology·2026
Same journal

Quantifying the counter-intuitive effects of vaccination by coupling the transmission dynamics of COVID-19 and the evolution of human behaviors.

Journal of theoretical biology·2026
Same journal

An integrative model of FGF2-induced signaling and muscle cell proliferation.

Journal of theoretical biology·2026
Same journal

A hybrid reaction-diffusion and mechanical stimulus model for mandibular bone remodeling under chewing and vibratory loading.

Journal of theoretical biology·2026
Same journal

Integrated tick management strategies in fragmented peridomestic environments.

Journal of theoretical biology·2026
Same journal

Joint likelihood-free inference of the number of selected single nucleotide polymorphisms and their selection coefficients in an evolving population.

Journal of theoretical biology·2026
See all related articles

Analyzing protein sequences reveals novel correlations. New property codes derived from sequence data show similarities to hydrophobicity and alpha-helix propensity, aiding in understanding protein structure.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Protein Science

Background:

  • Protein sequence analysis is crucial for understanding protein function and structure.
  • Traditional methods rely on physicochemical properties, but data-driven approaches offer new insights.

Purpose of the Study:

  • To identify novel correlations within large sets of non-homologous protein sequences.
  • To develop new property codes directly from sequence data using computational methods.

Main Methods:

  • Calculation of correlation functions on numerical mappings of protein sequences.
  • Testing various physicochemical property codes (e.g., hydrophobicity, alpha-helix propensity).
  • Utilizing Monte Carlo simulations to discover optimal sequence-to-number mappings.

Related Experiment Videos

Main Results:

  • Identified strong oscillating autocorrelation for hydrophobicity and decaying autocorrelation for alpha-helix propensity.
  • Detected patterns of alternating charged residues at specific distances (3-4 amino acids).
  • Discovered two novel property codes through cluster analysis of Monte Carlo simulations, related to hydrophobicity and alpha-helix propensity.

Conclusions:

  • Novel property codes can be effectively derived solely from protein sequence data.
  • These data-driven codes show similarities to established physicochemical properties.
  • The findings offer new tools for protein sequence analysis and structure prediction.