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

Framework for kernel regularization with application to protein clustering.

Fan Lu1, Sündüz Keles, Stephen J Wright

  • 1Department of Statistics, University of Wisconsin, Madison, WI 53706, USA.

Proceedings of the National Academy of Sciences of the United States of America
|August 20, 2005
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

Discovery and Optimization of Pyrazole Amides as Inhibitors of ELOVL1.

Journal of medicinal chemistry·2021
Same author

Comparative phylogeography study reveals introgression and incomplete lineage sorting during rapid diversification of Rhodiola.

Annals of botany·2021
Same author

Prioritizing natural-selection signals from the deep-sequencing genomic data suggests multi-variant adaptation in Tibetan highlanders.

National science review·2021
Same author

Visual acuity is correlated with ischemia and neurodegeneration in patients with early stages of diabetic retinopathy.

Eye and vision (London, England)·2021
Same author

A neglected transport of plastic debris to cities from farmland in remote arid regions.

The Science of the total environment·2021
Same author

Fate of a biobased polymer via high-solid anaerobic co-digestion with food waste and following aerobic treatment: Insights on changes of polymer physicochemical properties and the role of microbial and fungal communities.

Bioresource technology·2021
Same journal

The TaMYB55-TaSnRK1α1-TabZIP9 module confers heat stress tolerance in wheat.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same journal

Superstatistics approach to turbulent circulation fluctuations.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same journal

A molecular timescale for evolution of cobamide biosynthesis.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same journal

Pierre Chambon, a pioneer of molecular biology and gene regulation in eukaryotes.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same journal

Granulosa cell glycogen fuels the avascular corpus luteum.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same journal

Synthetic essentiality of TRAIL/TNFSF10 in VHL-deficient renal cell carcinoma.

Proceedings of the National Academy of Sciences of the United States of America·2026
See all related articles

This study introduces a new framework to create kernel matrices from noisy data, enabling better data visualization and analysis for tasks like protein clustering.

Area of Science:

  • Computational biology
  • Machine learning
  • Data analysis

Background:

  • Extracting meaningful patterns from complex, noisy datasets is a significant challenge.
  • Existing methods may struggle with incomplete or inconsistent dissimilarity information.

Purpose of the Study:

  • To develop a novel framework for generating positive definite kernel matrices from imperfect dissimilarity data.
  • To create a method that yields coordinates suitable for visualization and downstream machine learning tasks.

Main Methods:

  • Formulation of the problem as a convex optimization task.
  • Efficient solution using convex cone programming software.
  • Application to protein sequence data for clustering.

Main Results:

Related Experiment Videos

  • Successfully extracted a positive definite kernel matrix from protein sequence dissimilarities.
  • Generated a 3D Euclidean space representation of the globin protein family.
  • Identified known subfamilies and groupings within the globin dataset.

Conclusions:

  • The developed framework effectively handles noisy and incomplete data for kernel matrix construction.
  • The resulting coordinate system is valuable for visualizing complex biological data and improving classification/clustering.
  • This approach offers a powerful tool for analyzing biological sequences and other complex datasets.