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 Concept Videos

DNA Microarrays02:34

DNA Microarrays

Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...
Microsoft Excel: Regression Analysis01:18

Microsoft Excel: Regression Analysis

Regression analysis in Microsoft Excel is a powerful statistical method for examining the relationship between a dependent variable and one or more independent variables. It's used extensively in fields such as economics, biology, and business to predict outcomes, understand relationships, and make data-driven decisions. The most common type is linear regression, which attempts to fit a straight line through the data points to model the relationship between variables.
To perform regression...
Survival Tree01:19

Survival Tree

Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
Constructing a survival tree begins...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Beyond the Tip of the Iceberg: The Clinical Impact of Maternal Nonprimary Cytomegalovirus Infection.

The Pediatric infectious disease journal·2026
Same author

Clinical Characteristics of Campylobacter Bacteremia in Pediatric Population.

Clinical pediatrics·2026
Same author

Visual Right Ventricular Assessment in ICU: A Multicenter International Study.

Critical care medicine·2026
Same author

Ventricular arrhythmia ablation timing and outcomes in electrical STORM requiring V-A ECMO support: the STORM-ECMO study.

Critical care (London, England)·2026
Same author

Polarization-Resolved Speckle Technique for Rapid Non-Destructive Characterization of Macroporous Silica Thin Films.

Sensors (Basel, Switzerland)·2026
Same author

Effect of femoro-axillary V-A ECMO flow on pulmonary capillary wedge pressure.

Critical care (London, England)·2026

Related Experiment Video

Updated: Jun 22, 2026

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

Study of microarray time series data based on Forward-Backward Linear Prediction and Singular Value Decomposition.

Miew Keen Choong1, David Levy, Hong Yan

  • 1School of Electrical and Information Engineering, The University of Sydney, NSW 2006, Australia. miewkeen@ee.usyd.edu.au

International Journal of Data Mining and Bioinformatics
|June 13, 2009
PubMed
Summary
This summary is machine-generated.

We developed a new spectral reconstruction method to analyze gene expression periodicities without prior knowledge. This approach accurately estimates peak frequencies, outperforming existing methods for cell-cycle regulation studies.

More Related Videos

Comprehensive Spatial Profiling of Species-agnostic Transcriptomes via Stereo-seq
10:22

Comprehensive Spatial Profiling of Species-agnostic Transcriptomes via Stereo-seq

Published on: October 31, 2025

The Terroir Concept Interpreted through Grape Berry Metabolomics and Transcriptomics
13:02

The Terroir Concept Interpreted through Grape Berry Metabolomics and Transcriptomics

Published on: October 5, 2016

Related Experiment Videos

Last Updated: Jun 22, 2026

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

Comprehensive Spatial Profiling of Species-agnostic Transcriptomes via Stereo-seq
10:22

Comprehensive Spatial Profiling of Species-agnostic Transcriptomes via Stereo-seq

Published on: October 31, 2025

The Terroir Concept Interpreted through Grape Berry Metabolomics and Transcriptomics
13:02

The Terroir Concept Interpreted through Grape Berry Metabolomics and Transcriptomics

Published on: October 5, 2016

Area of Science:

  • Bioinformatics
  • Systems Biology
  • Computational Biology

Background:

  • Gene expression profiles exhibit periodic patterns crucial for understanding cellular processes.
  • Accurate analysis of these periodicities is essential for studying cell-cycle regulation.
  • Existing methods often require significant prior biological knowledge.

Purpose of the Study:

  • To propose a novel spectral domain method for analyzing gene expression periodicities.
  • To demonstrate the method's effectiveness in the absence of prior knowledge.
  • To improve the accuracy of spectral frequency estimation in biological signals.

Main Methods:

  • Spectral reconstruction using a spectral domain approach.
  • Combining signals with similar frequency components to form overdetermined systems.
  • Least squares solutions for estimating spectral frequencies.

Main Results:

  • The proposed spectral reconstruction method outperforms three other recently proposed methods.
  • The method successfully analyzes cell-cycle regulation with minimal prior knowledge.
  • Accurate estimation of peak spectral frequency was achieved.

Conclusions:

  • A robust method for analyzing gene expression periodicities has been developed.
  • This approach offers a valuable tool for studying cell-cycle regulation, especially with limited prior information.
  • The spectral domain approach provides enhanced accuracy in frequency estimation.