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

Fast Fourier Transform01:10

Fast Fourier Transform

287
The Fast Fourier Transform (FFT) is a computational algorithm designed to compute the Discrete Fourier Transform (DFT) efficiently. By breaking down the calculations into smaller, manageable sections, the FFT significantly reduces the computational complexity involved. Direct computation of an N-point DFT requires N2 complex multiplications, whereas the FFT algorithm needs only (N/2)log⁡2N multiplications, offering a much faster performance.
The computational efficiency of the FFT becomes...
287
Magnetic Resonance Imaging01:24

Magnetic Resonance Imaging

5.0K
Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...
5.0K
Continuous -time Fourier Transform01:11

Continuous -time Fourier Transform

304
The Fourier series is instrumental in representing periodic functions, offering a powerful method to decompose such functions into a sum of sinusoids. This technique, however, necessitates modification when applied to nonperiodic functions. Consider a pulse-train waveform consisting of a series of rectangular pulses. When these pulses have a finite period, they can be accurately represented by a Fourier series. Yet, as the period approaches infinity, resulting in a single, isolated pulse, the...
304
Discrete Fourier Transform01:15

Discrete Fourier Transform

229
The Discrete Fourier Transform (DFT) is a fundamental tool in signal processing, extending the discrete-time Fourier transform by evaluating discrete signals at uniformly spaced frequency intervals. This transformation converts a finite sequence of time-domain samples into frequency components, each representing complex sinusoids ordered by frequency. The DFT translates these sequences into the frequency domain, effectively indicating the magnitude and phase of each frequency component present...
229
Basic signals of Fourier Transform01:07

Basic signals of Fourier Transform

481
The Fourier Transform is a pivotal mathematical tool in signal processing, enabling the transformation of time-domain signals into their frequency-domain representations. Among the numerous elements within this domain, certain functions like the sinc function, delta function, and exponential signals hold significant importance due to their unique properties and implications.
The sinc function, defined as sinc(x) = sin(πx)/(πx), is particularly notable for its symmetry and behavior at...
481
Properties of Fourier Transform II01:24

Properties of Fourier Transform II

185
The Fourier Transform (FT) is an essential mathematical tool in signal processing, transforming a time-domain signal into its frequency-domain representation. This transformation elucidates the relationship between time and frequency domains through several properties, each revealing unique aspects of signal behavior.
The Frequency Shifting property of Fourier Transforms highlights that a shift in the frequency domain corresponds to a phase shift in the time domain. Mathematically, if x(t) has...
185

You might also read

Related Articles

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

Sort by
Same author

SLECA: A Single-Cell Atlas of Systemic Lupus Erythematosus Enabling Rare-Cell Discovery Using Graph Transformer.

Computational and structural biotechnology journal·2026
Same author

Safety and clinical outcomes of a first-in-human trial of point-of-care manufactured trispecific CAR T cells targeting CD19, CD20, and CD22.

Blood cancer discovery·2026
Same author

CD22 is upregulated and displays suppressive properties on CD4+ T cells upon a persistent virus infection.

Journal of immunology (Baltimore, Md. : 1950)·2026
Same author

Sphingosine 1-phosphate lyase expressed in pulmonary epithelial cells potentiates host innate defenses and alleviates influenza pathogenicity in mice.

bioRxiv : the preprint server for biology·2026
Same author

Dynamic multivariate patterns of brain structure-neuropsychiatric symptom associations in long COVID.

Brain communications·2026
Same author

Leuconostoc pseudomesenteroides YT830: a promising lactic acid bacterial starter culture for synbiotic fermented yak milk products as revealed by metabolic and genomic analyses.

Journal of applied microbiology·2026

Related Experiment Video

Updated: Jun 14, 2025

Morphology-Based Distinction Between Healthy and Pathological Cells Utilizing Fourier Transforms and Self-Organizing Maps
08:59

Morphology-Based Distinction Between Healthy and Pathological Cells Utilizing Fourier Transforms and Self-Organizing Maps

Published on: October 28, 2018

7.1K

Graph Fourier transform for spatial omics representation and analyses of complex organs.

Yuzhou Chang1,2, Jixin Liu3, Yi Jiang1

  • 1Department of Biomedical Informatics, College of Medicine, Ohio State University, Columbus, OH, 43210, USA.

Nature Communications
|August 29, 2024
PubMed
Summary

Spatial Graph Fourier Transform (SpaGFT) offers a new graph signal processing method for spatial omics data. It enhances gene identification and imputation, outperforming existing tools for tissue biology exploration.

More Related Videos

High-Throughput Analysis of Optical Mapping Data Using ElectroMap
07:36

High-Throughput Analysis of Optical Mapping Data Using ElectroMap

Published on: June 4, 2019

9.3K
Multispectral Optoacoustic Tomography for Functional Imaging in Vascular Research
06:40

Multispectral Optoacoustic Tomography for Functional Imaging in Vascular Research

Published on: June 8, 2022

1.8K

Related Experiment Videos

Last Updated: Jun 14, 2025

Morphology-Based Distinction Between Healthy and Pathological Cells Utilizing Fourier Transforms and Self-Organizing Maps
08:59

Morphology-Based Distinction Between Healthy and Pathological Cells Utilizing Fourier Transforms and Self-Organizing Maps

Published on: October 28, 2018

7.1K
High-Throughput Analysis of Optical Mapping Data Using ElectroMap
07:36

High-Throughput Analysis of Optical Mapping Data Using ElectroMap

Published on: June 4, 2019

9.3K
Multispectral Optoacoustic Tomography for Functional Imaging in Vascular Research
06:40

Multispectral Optoacoustic Tomography for Functional Imaging in Vascular Research

Published on: June 8, 2022

1.8K

Area of Science:

  • Genomics
  • Computational Biology
  • Bioinformatics

Background:

  • Spatial omics technologies reveal cellular and subcellular details in complex organs.
  • Interpretable representations are crucial for analyzing complex spatial omics data.

Purpose of the Study:

  • To introduce Spatial Graph Fourier Transform (SpaGFT) for analyzing diverse spatial omics platforms.
  • To enhance spatially variable gene identification and gene expression imputation.
  • To provide an explainable graph representation for tissue biology exploration.

Main Methods:

  • Applied graph signal processing to spatial omics data.
  • Developed Spatial Graph Fourier Transform (SpaGFT) for interpretable data representation.
  • Integrated SpaGFT with machine learning frameworks.

Main Results:

  • SpaGFT outperforms existing tools in human and mouse spatial transcriptomics data analysis.
  • Identified immunological regions for B cell maturation and characterized secondary follicles.
  • Improved spatial domain identification, cell type annotation, and subcellular feature inference by up to 40%.
  • Detected rare subcellular organelles in spatial proteomics data.

Conclusions:

  • SpaGFT provides an effective and explainable method for spatial omics data analysis.
  • The approach enhances the understanding of tissue biology and function at multiple resolutions.
  • SpaGFT is a versatile tool applicable to various spatial omics profiling platforms.