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

An extensible automated protein annotation tool: standardizing input and output using validated XML.

S Vishnu V Deevi1, Andrew C R Martin

  • 1School of Animal and Microbial Sciences, The University of Reading, P.O. Box 228, Whiteknights, Reading RG6 6AJ, UK.

Bioinformatics (Oxford, England)
|December 13, 2005
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

An antibody developability triaging pipeline exploiting protein language models.

mAbs·2025
Same author

Enhancing missense variant pathogenicity prediction with protein language models using VariPred.

Scientific reports·2024
Same author

Do antibody CDR loops change conformation upon binding?

mAbs·2024
Same author

abYpap: improvements to the prediction of antibody VH/VL packing using gradient boosted regression.

Protein engineering, design & selection : PEDS·2023
Same author

Antibody markup language (AbML) - a notation language for antibody-based drug formats and software for creating and rendering AbML (abYdraw).

mAbs·2022
Same author

GraphQL for the delivery of bioinformatics web APIs and application to ZincBind.

Bioinformatics advances·2022
Same journal

Biomedical Concept Recognition with Error-aware Negative-enhanced Ranking Framework.

Bioinformatics (Oxford, England)·2026
Same journal

TEDLH: Domain HMMs for sensitive detection of remote homologues.

Bioinformatics (Oxford, England)·2026
Same journal

PLNFGL: Joint Estimation of Multi-Condition Gene Networks from Single-cell RNA-seq Data.

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

A new tool dispatches biological sequences to various prediction and annotation services using a standardized XML format. This system streamlines the analysis of sequence data, making it more accessible for researchers.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Researchers frequently require diverse local or remote prediction and annotation tools for sequence analysis.
  • Existing tools often lack a unified data format, hindering interoperability.

Purpose of the Study:

  • To develop a tool for dispatching sequences to multiple services.
  • To establish a consistent XML format for sequence data and annotations.

Main Methods:

  • Designed XML Document Type Definitions (DTDs) to standardize input and output for annotation servers.
  • Developed plug-in wrappers for various services, integrated via a master script.
  • Formatted output (APATML) for HTML display and further post-analysis.

Main Results:

Related Experiment Videos

  • Annotations were categorized into six data forms: numeric/textual for residues, domains, or whole sequences.
  • A flexible XML structure was created to accommodate diverse annotation types.
  • The system successfully integrated multiple annotation services.

Conclusions:

  • The developed tool and XML format enable efficient and standardized analysis of biological sequences.
  • This approach enhances the utility of various prediction and annotation services by improving data integration.