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

Iterative gene prediction and pseudogene removal improves genome annotation.

Marijke J van Baren1, Michael R Brent

  • 1Laboratory for Computational Genomics, Department of Computer Science Washington University, Saint Louis, Missouri 63130, USA.

Genome Research
|May 3, 2006
PubMed
Summary

Processed pseudogenes, nonfunctional gene copies, hinder accurate gene prediction. PPFINDER (Processed Pseudogene finder) software effectively removes these pseudogenes, significantly improving gene prediction accuracy in mammals.

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

Finding Significant Hits in Networks: a network-based tool for analyzing gene-level P-values to identify significant genes missed by standard methods.

Briefings in bioinformatics·2026
Same author

UBIQUITOUS FUNCTIONAL SYNERGY PARTIALLY EXPLAINS WHY MOST TRANSCRIPTION FACTOR BINDING IS NON-FUNCTIONAL.

bioRxiv : the preprint server for biology·2026
Same author

Mapping the transcriptional regulatory network of a fungal pathogen by exploiting transcription factor perturbation.

mBio·2025
Same author

Combining Motifs, CRE Activity, And Gene Expression Data Using ML Greatly Improves the Accuracy of Tissue-Specific TF Network Maps.

bioRxiv : the preprint server for biology·2025
Same author

The UCSC Genome Browser database: 2026 update.

Nucleic acids research·2025
Same author

Mapping the transcriptional regulatory network of a fungal pathogen by exploiting transcription factor perturbation.

bioRxiv : the preprint server for biology·2025

Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Processed pseudogenes are nonfunctional, intronless copies of genes that can interfere with accurate gene prediction.
  • Existing gene prediction tools often misidentify processed pseudogenes as functional genes or exons, leading to biologically irrelevant results.
  • Current methods for pseudogene identification are not integrated with gene prediction pipelines.

Purpose of the Study:

  • To develop a novel computational tool, PPFINDER (Processed Pseudogene finder), for identifying and removing processed pseudogenes from genomic annotations.
  • To integrate pseudogene removal into the gene prediction process to enhance accuracy.
  • To create a standalone tool for identifying erroneous gene predictions caused by pseudogenes.

Main Methods:

Related Experiment Videos

  • PPFINDER integrates multiple computational methods for processed pseudogene identification in mammalian genomes.
  • The study interleaves pseudogene masking with N-SCAN gene predictions to improve accuracy.
  • PPFINDER was utilized with gene predictions as a parent database, removing the dependency on known gene libraries.

Main Results:

  • Integration of PPFINDER with gene prediction significantly improves the accuracy of gene identification.
  • The interleaved gene prediction and pseudogene masking approach leads to substantial enhancements in gene prediction quality.
  • PPFINDER enables gene prediction on newly sequenced genomes with limited known gene data.

Conclusions:

  • PPFINDER is an effective tool for identifying and removing processed pseudogenes, crucial for accurate gene prediction.
  • Interleaving gene prediction with pseudogene masking is a superior strategy for improving genomic annotation.
  • The PPFINDER approach facilitates gene prediction in novel genomes, advancing genomic research.