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

Global gene expression analysis by combinatorial optimization.

Adam Ameur1, Erik Aurell, Mats Carlsson

  • 1SICS, Swedish Institute of Computer Science, P.O. Box 1263, S-164 29 Kista, Sweden.

In Silico Biology
|April 27, 2004
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

Whole-genome sequencing with AVITI and NovaSeq X Plus reveals comparable performance with contextual biases.

NAR genomics and bioinformatics·2026
Same author

Fitness inference tested by in silico population genetics.

Physical review. E·2026
Same author

Nallo: a Nextflow pipeline for comprehensive human long-read genome analysis.

Bioinformatics (Oxford, England)·2026
Same author

Avalanches in magnetohydrodynamical simulations.

Physical review. E·2026
Same author

Fitness inference tested by in silico population genetics.

ArXiv·2025
Same author

Single cell long read whole genome sequencing reveals somatic transposon activity in human brain.

Communications biology·2025
Same journal

Regulatory Effects of Cooperativity and Signal Profile on Adaptive Dynamics in Incoherent Feedforward Loop Networks.

In silico biology·2025
Same journal

scAN1.0: A reproducible and standardized pipeline for processing 10X single cell RNAseq data.

In silico biology·2023
Same journal

Modelling speciation: Problems and implications.

In silico biology·2022
Same journal

Where Do CABs Exist? Verification of a specific region containing concave Actin Bundles (CABs) in a 3-Dimensional confocal image.

In silico biology·2022
Same journal

Network analysis of host-pathogen protein interactions in microbe induced cardiovascular diseases.

In silico biology·2022
Same journal

Multiscale modeling of tumor response to vascular endothelial growth factor (VEGF) inhibitor.

In silico biology·2022
See all related articles

This study enhances gene expression profiling by using advanced data post-processing to achieve global coverage with high accuracy. The method overcomes the precision-versus-scale trade-off common in gene expression analysis.

Area of Science:

  • Genomics
  • Molecular Biology
  • Bioinformatics

Background:

  • Gene expression analysis methods often present a trade-off between precision (e.g., RT-PCR) and global coverage (e.g., microarrays).
  • Existing quantitative gene expression profiling methods can be labor-intensive, limiting their scalability.

Purpose of the Study:

  • To develop a method for global gene expression measurement with high accuracy.
  • To adapt a known gene expression profiling technique for large-scale quantitative analysis.
  • To address the limitations of current gene expression analysis tools.

Main Methods:

  • Utilized advanced data post-processing techniques, specifically solving a combinatorial optimization problem.
  • Adapted a previously established gene expression profiling method (Kato et al., 1995).

Related Experiment Videos

  • Validated the approach using in silico experiments from the FANTOM mouse cDNA database.

    • Main Results:

    • Demonstrated that a labor-intensive gene expression profiling method can be transformed into a global measurement tool with minimal accuracy loss.
    • Developed two variants of the post-processing method: one using commercial software and another with a custom-developed, publicly available code.
    • Successfully applied advanced computational methods to enhance gene expression data analysis.

    Conclusions:

    • Advanced data post-processing can bridge the gap between precise and global gene expression analysis methods.
    • The developed computational approach offers a scalable and accurate solution for gene expression profiling.
    • The availability of both commercial and open-source solutions facilitates broader adoption in genomic research.