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

Handling missing DNA microarray data by kriging estimators.

Tuan D Pham1

  • 1Bioinformatics Applications Research Centre, School of Information Technology, James Cook University, Townsville, Queensland 4811, Australia.

International Journal of Bioinformatics Research and Applications
|December 1, 2007
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

Explainable Knowledge-Guided Algorithm for Contrast Extravasation Detection on Computed Tomography.

IEEE journal of translational engineering in health and medicine·2026
Same author

Classification of pediatric dental diseases from panoramic radiographs using natural language transformer and deep learning models.

Frontiers in artificial intelligence·2026
Same author

Stomatognathic Diseases Reveal Bidirectional Link Between Diabetes Mellitus and Coronary Artery Calcium: A Cross-Sectional Study Using Multi-Way Array Analysis.

Health science reports·2025
Same author

Impact of tooth loss and patient characteristics on coronary artery calcium score classification and prediction.

Scientific reports·2024
Same author

Exploring nonlinear dynamics in brain functionality through phase portraits and fuzzy recurrence plots.

Chaos (Woodbury, N.Y.)·2024
Same author

Artificial Intelligence in Head and Neck Cancer: Innovations, Applications, and Future Directions.

Current oncology (Toronto, Ont.)·2024
Same journal

In silico analysis, annotation and characterisation of putative ESTs from Sorghum bicolor associated with heat stress.

International journal of bioinformatics research and applications·2015
Same journal

Docking analysis of gallic acid derivatives as HIV-1 protease inhibitors.

International journal of bioinformatics research and applications·2015
Same journal

Automatic segmentation of Potyviridae family polyproteins.

International journal of bioinformatics research and applications·2015
Same journal

Neural network and rough set hybrid scheme for prediction of missing associations.

International journal of bioinformatics research and applications·2015
Same journal

On the interconnection of stable protein complexes: inter-complex hubs and their conservation in Saccharomyces cerevisiae and Homo sapiens networks.

International journal of bioinformatics research and applications·2015
Same journal

Diversity and evolution of the envelope gene of dengue virus type 1 circulating in India in recent times.

International journal of bioinformatics research and applications·2015
See all related articles

Researchers can now better analyze gene expression data. Two new kriging methods effectively estimate missing values in DNA microarrays, improving data quality for gene recognition efforts.

Area of Science:

  • Bioinformatics
  • Genomics
  • Computational Biology

Background:

  • Microarray gene expression data offer detailed insights into gene expression patterns.
  • Conventional methods are limited, and microarray data often contain missing values due to technical limitations like noise and low image resolution.
  • Accurate imputation of missing data is crucial for reliable downstream analysis.

Purpose of the Study:

  • To introduce novel methods for estimating missing values in DNA microarray datasets.
  • To enhance the usability of gene expression matrices for further biological interpretation and gene recognition.

Main Methods:

  • Development and application of two distinct kriging-based estimators.
  • Utilizing geostatistical principles for imputing missing elements in gene expression matrices.

Related Experiment Videos

Main Results:

  • The proposed kriging estimators demonstrate effectiveness in handling missing data points within microarray experiments.
  • The methods provide a robust approach to data imputation, thereby improving the integrity of gene expression matrices.

Conclusions:

  • The presented kriging estimators are valuable tools for addressing missing data challenges in DNA microarrays.
  • These methods facilitate more comprehensive and accurate downstream analyses of gene expression data, aiding in gene recognition efforts.