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

Engene: the processing and exploratory analysis of gene expression data.

Jorge García de la Nava1, Daniel Franco Santaella, Jesús Cuenca Alba

  • 1Computer Architecture Department, Universidad de Málaga, 29080 Málaga, Spain.

Bioinformatics (Oxford, England)
|March 26, 2003
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

Membrane and vesicle structure detection in cryo-electron tomography based on deep learning.

Journal of structural biology·2025
Same author

Merging conformational landscapes in a single consensus space with FlexConsensus algorithm.

Nature methods·2025
Same author

Real-space heterogeneous reconstruction, refinement, and disentanglement of CryoEM conformational states with HetSIREN.

Nature communications·2025
Same author

On interrogating electron microscopy images to discover proteins in the cell.

IUCrJ·2025
Same author

Correction to "Dissecting the Conformational Heterogeneity of Stem-Loop Substructures of the Fifth Element in the 5'-Untranslated Region of SARS-CoV-2".

Journal of the American Chemical Society·2025
Same author

Dissecting the Conformational Heterogeneity of Stem-Loop Substructures of the Fifth Element in the 5'-Untranslated Region of SARS-CoV-2.

Journal of the American Chemical Society·2024
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

Engene provides a versatile, platform-independent web tool for exploring gene expression data. It facilitates the storage, visualization, and processing of extensive gene expression patterns.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Gene expression data analysis is crucial for understanding biological processes.
  • Existing tools may lack versatility or platform independence.
  • Efficiently managing and visualizing large datasets is a significant challenge.

Purpose of the Study:

  • To introduce Engene, a novel web tool for exploratory gene expression data analysis.
  • To provide a platform-independent solution for storing, visualizing, and processing gene expression patterns.
  • To enhance the accessibility and efficiency of genomic data exploration.

Main Methods:

  • Development of a versatile, platform-independent web-based application.
  • Implementation of functionalities for data storage, visualization, and processing.

Related Experiment Videos

  • Focus on handling large sets of gene expression patterns.

    • Main Results:

    • Engene offers a user-friendly interface for exploratory data analysis.
    • The tool supports efficient storage and retrieval of diverse gene expression datasets.
    • Visualization capabilities enable intuitive exploration of gene expression patterns.

    Conclusions:

    • Engene serves as a valuable resource for researchers analyzing gene expression data.
    • Its platform independence and versatility make it broadly applicable in genomics.
    • The tool streamlines the process of discovering insights from complex gene expression patterns.