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

Dynameomics: a multi-dimensional analysis-optimized database for dynamic protein data.

Catherine Kehl1, Andrew M Simms, Rudesh D Toofanny

  • 1Biomedical and Health Informatics Program, Department of Bioengineering, University of Washington, Seattle, WA 98195-5013, USA.

Protein Engineering, Design & Selection : PEDS
|April 16, 2008
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

Drug Development.

Alzheimer's & dementia : the journal of the Alzheimer's Association·2025
Same author

Layer-By-Layer Functionalized Gauze With Designed α-Sheet Peptides Inhibits E. coli and S. aureus Biofilm Formation.

Journal of biomedical materials research. Part A·2025
Same author

Designed De Novo α-Sheet Peptides Destabilize Bacterial Biofilms and Increase the Susceptibility of <i>E. coli</i> and <i>S. aureus</i> to Antibiotics.

International journal of molecular sciences·2024
Same author

Performance of SOBA-AD blood test in discriminating Alzheimer's disease patients from cognitively unimpaired controls in two independent cohorts.

Scientific reports·2024
Same author

Mechanistic insights into the role of amyloid-β in innate immunity.

Scientific reports·2024
Same author

A patient safety knowledge graph supporting vaccine product development.

BMC medical informatics and decision making·2024
Same journal

Combining bacterial display and protein language models to engineer a CD69-binding affibody for molecular imaging of immune activation.

Protein engineering, design & selection : PEDS·2026
Same journal

Examining selection dynamics and limitations in multi-round protein selection of high diversity libraries.

Protein engineering, design & selection : PEDS·2026
Same journal

A photo-enhanced oxidative coupling for site-specific protein Labeling via noncanonical amino acid incorporation.

Protein engineering, design & selection : PEDS·2026
Same journal

Engineering affibody domains as anti-idiotypic masks for nivolumab-based prodrugs.

Protein engineering, design & selection : PEDS·2026
Same journal

Integrating machine learning tools in protein design: a case of MHETase engineering for PET biodeconstruction.

Protein engineering, design & selection : PEDS·2026
Same journal

Computational redesign of a thermostable T7 RNA polymerase.

Protein engineering, design & selection : PEDS·2026
See all related articles

The Dynameomics project uses On-line Analytical Processing (OLAP) to analyze large, complex protein dynamics data. This approach offers efficient data retrieval and analysis for bioengineering and biomedical applications.

Area of Science:

  • Computational Biology
  • Bioinformatics
  • Data Science

Background:

  • The Dynameomics project aims to characterize protein dynamics and folding pathways using extensive molecular dynamics simulations.
  • Simulation data is large (multi-terabytes) and multidimensional, posing significant storage, retrieval, and analysis challenges.

Purpose of the Study:

  • To identify a suitable data analysis platform for large, multidimensional protein dynamics data.
  • To leverage the capabilities of On-line Analytical Processing (OLAP) for scientific data analysis.

Main Methods:

  • Utilized molecular dynamics simulations to generate protein dynamics data.
  • Implemented On-line Analytical Processing (OLAP) database technology for data storage and analysis.
  • Focused on OLAP's multidimensional indexing and hierarchical data modeling capabilities.

Related Experiment Videos

Main Results:

  • OLAP provides a flexible dimensional data model and concise query language for complex analysis.
  • OLAP enables rapid data retrieval from large, multidimensional datasets.
  • Demonstrated OLAP's suitability for analyzing protein dynamics data.

Conclusions:

  • OLAP is a promising analytical platform for dynamic protein analysis in bioengineering and biomedical fields.
  • OLAP's capabilities may extend to other scientific and engineering applications with large, complex datasets.