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

A simple probabilistic scoring method for protein domain identification.

J Murvai1, K Vlahovicek, S Pongor

  • 1Protein Structure and Function Group, International Centre for Genetic Engineering and Biotechnology, Area Science Park, 34012 Trieste, Italy. murvai@icgeb.trieste.it

Bioinformatics (Oxford, England)
|February 13, 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

Selection and design of high affinity DNA ligands for mutant single-chain derivatives of the bacteriophage 434 repressor.

Science in China. Series C, Life sciences·2008
Same author

Design of peptide mimetics of HIV-1 gp120 for prevention and therapy of HIV disease.

The journal of peptide research : official journal of the American Peptide Society·2003
Same author

Structural analysis of free and enzyme-bound amaranth alpha-amylase inhibitor: classification within the knottin fold superfamily and analysis of its functional flexibility.

Protein engineering·2001
Same author

Arginine methylation of a mitochondrial guide RNA binding protein from Trypanosoma brucei.

Molecular and biochemical parasitology·2001
Same author

Proteins of circularly permuted sequence present within the same organism: the major serine proteinase inhibitor from Capsicum annuum seeds.

Protein science : a publication of the Protein Society·2001
Same author

Modular construction of extended DNA recognition surfaces: mutant DNA-binding domains of the 434 repressor as building blocks.

Protein engineering·2001
Same journal

MCFST: Spatial domain identification method based on multi-view graph convolutional network and graph fusion network.

Bioinformatics (Oxford, England)·2026
Same journal

SpaBiT: Enhancing Spatial Transcriptomics Resolution via Bidirectional Attention Transformers.

Bioinformatics (Oxford, England)·2026
Same journal

EDEL: Enhancing Dense Retrievers for Curation of Biomedical Knowledge Bases.

Bioinformatics (Oxford, England)·2026
Same journal

Informative Relational Learning for Adverse Reaction Prediction with Enhanced Generalization to Novel Drugs.

Bioinformatics (Oxford, England)·2026
Same journal

An interpretable deep learning framework uncovers features governing CRISPR-Cas9 genome-editing efficiency.

Bioinformatics (Oxford, England)·2026
Same journal

3DICE: Interpretable 3D Cross-Modal Learning for Drug-Target Interaction Prediction and Large-Scale Drug Discovery.

Bioinformatics (Oxford, England)·2026
See all related articles

A new scoring method simplifies assigning sequences to protein domain types using BLAST search results. This heuristic approach analyzes score distributions for efficient domain identification.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Structural Biology

Background:

  • Accurate protein domain identification is crucial for understanding protein function and evolution.
  • Existing methods for domain assignment can be computationally intensive or lack precision.

Purpose of the Study:

  • To develop a simple and efficient heuristic scoring method for assigning biological sequences to known protein domain types.
  • To leverage outputs from Basic Local Alignment Search Tool (BLAST) searches for automated domain classification.

Main Methods:

  • A heuristic scoring system was devised based on analyzing score distributions.
  • Database-versus-database comparisons were used to establish reference score distributions for known domain groups.
  • The method directly processes and interprets BLAST search outputs.

Related Experiment Videos

Main Results:

  • The described scoring method provides a straightforward way to classify sequences into predefined domain categories.
  • The approach is directly applicable to the raw output generated by BLAST searches.
  • The method's efficacy relies on the statistical properties of BLAST scores derived from comprehensive comparisons.

Conclusions:

  • A simple heuristic scoring method enables accurate assignment of sequences to known domain types.
  • The method utilizes BLAST search outputs and score distributions for efficient domain identification.
  • This approach offers a practical solution for processing large-scale sequence data in bioinformatics.