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

Computational aspects of expression data

M Vingron1, J Hoheisel

  • 1Deutsches Krebsforschungszentrum, Heidelberg, Germany. m.vingron@dkfz-heidelberg.de

Journal of Molecular Medicine (Berlin, Germany)
|February 4, 1999
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

Stochastics of Cellular Differentiation Explained by Epigenetics: The Case of T-Cell Differentiation and Functional Plasticity.

Scandinavian journal of immunology·2017
Same author

X-exome sequencing of 405 unresolved families identifies seven novel intellectual disability genes.

Molecular psychiatry·2015
Same author

Early epigenetic downregulation of WNK2 kinase during pancreatic ductal adenocarcinoma development.

Oncogene·2013
Same author

Hypermethylation of TUSC5 genes in breast cancer tissue.

Experimental oncology·2013
Same author

Anti-inflammatory and anti-cancer activities of essential oils and their biological constituents.

International journal of clinical pharmacology and therapeutics·2010
Same author

Identification of immunohistochemical prognostic markers for survival after resection of pulmonary metastases from colorectal carcinoma.

The Thoracic and cardiovascular surgeon·2009
Same journal

Integrative genetic and functional analysis of autosomal dominant hearing loss in 108 multigenerational families.

Journal of molecular medicine (Berlin, Germany)·2026
Same journal

Preclinical evaluation of cysteine protease-inhibitor aloxistatin (E64d) for heart failure therapy.

Journal of molecular medicine (Berlin, Germany)·2026
Same journal

Zinc-binding protein metallothionein 3 protects vascular smooth muscle cells from ferroptosis via blocking lysosomal degradation of GPX4.

Journal of molecular medicine (Berlin, Germany)·2026
Same journal

Clinical utility of cerebrospinal fluid interleukin-10 in central nervous system lymphoma: a molecular neuropathology-informed diagnostic meta-analysis.

Journal of molecular medicine (Berlin, Germany)·2026
Same journal

Molecular regulation of PGC-1α: from protein-protein interactions and post-translational modifications to pharmacological modulation.

Journal of molecular medicine (Berlin, Germany)·2026
Same journal

Molecular determinants of thromboinflammatory activation in inflammatory bowel disease.

Journal of molecular medicine (Berlin, Germany)·2026
See all related articles

Analyzing gene expression data from cellular experiments presents challenges. This review explores computational methods to interpret large datasets generated by modern gene expression techniques.

Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Modern experimental techniques allow for the study of gene expression at a specific moment.
  • These methods generate substantial amounts of expression data.
  • Interpreting this large-scale data can be complex.

Purpose of the Study:

  • To review the computational questions and approaches related to gene expression data analysis.
  • To provide an overview of challenges and solutions in interpreting large expression datasets.

Main Methods:

  • Review of current experimental techniques for gene expression profiling.
  • Identification and categorization of computational challenges.
  • Survey of existing computational approaches and algorithms.

Related Experiment Videos

Main Results:

  • Gene expression studies yield vast, complex datasets.
  • Numerous computational challenges arise in data interpretation.
  • A range of computational strategies are employed to address these challenges.

Conclusions:

  • Computational approaches are crucial for understanding gene expression data.
  • Effective interpretation requires addressing specific computational questions.
  • Further development in computational methods will enhance biological insights from expression data.