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

PROSPECT improves cis-acting regulatory element prediction by integrating expression profile data with consensus

W Fujibuchi1, J S Anderson, D Landsman

  • 1Computational Biology Branch, National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 45 Center Drive, Bethesda, MD 20894, USA.

Nucleic Acids Research
|September 28, 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

Overdispersion models for correlated multinomial data: Applications to blinding assessment.

Statistics in medicine·2019
Same author

Increased Functional Connectivity After Listening to Favored Music in Adults With Alzheimer Dementia.

The journal of prevention of Alzheimer's disease·2018
Same author

Multivariate characterization of white matter heterogeneity in autism spectrum disorder.

NeuroImage. Clinical·2017
Same author

Dataset of Arabidopsis plants that overexpress FT driven by a meristem-specific KNAT1 promoter.

Data in brief·2016
Same author

Is there an exemplar taxon for modelling the evolution of early tetrapod hearing?

Proceedings. Biological sciences·2016
Same author

High-throughput synthesis and characterization of nanocrystalline porphyrinic zirconium metal-organic frameworks.

Chemical communications (Cambridge, England)·2016

This study introduces a new method to reduce false positives in identifying gene regulatory sequences by integrating gene expression data. The developed tool, PROSPECT, improves the accuracy of predicting transcriptional regulatory elements.

Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • Predicting cis-acting transcriptional regulatory sequences using consensus patterns often yields numerous false positives.
  • Existing methods lack sufficient specificity in identifying functional regulatory elements.

Purpose of the Study:

  • To decrease false positives in the prediction of transcriptional regulatory sequences.
  • To integrate gene expression profile data into existing consensus pattern-based search methods.

Main Methods:

  • Systematic analysis of expression phenotypes for over 6000 yeast genes across 121 experiments.
  • Correlation of gene expression phenotypes with the distribution of 14 known regulatory elements in upstream sequences.
  • Development of a metric termed probabilistic element assessment (PEA) for ranking potential regulatory sites.

Related Experiment Videos

Main Results:

  • The probabilistic element assessment (PEA) method demonstrated significantly higher selectivity compared to naive consensus pattern searches for eight out of 14 regulatory elements.
  • Integration of expression profile data effectively reduced false positives in predicting regulatory sequences.
  • A web-based tool, PROSPECT, was developed to facilitate searching gene clusters from microarray data.

Conclusions:

  • Incorporating gene expression data into sequence analysis is a powerful strategy for improving the accuracy of predicting transcriptional regulatory elements.
  • The PROSPECT tool offers a valuable resource for researchers studying gene regulation in yeast.
  • This approach enhances the reliability of identifying cis-acting regulatory sequences, advancing genomic research.