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

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data12:08

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

25.0K
The bottleneck for cellular 3D electron microscopy is feature extraction (segmentation) in highly complex 3D density maps. We have developed a set of criteria, which provides guidance regarding which segmentation approach (manual, semi-automated, or automated) is best suited for different data types, thus providing a starting point for effective...
25.0K
A Protocol of Manual Tests to Measure Sensation and Pain in Humans07:28

A Protocol of Manual Tests to Measure Sensation and Pain in Humans

21.6K
The goal of this procedure is to demonstrate a battery of quantitative techniques for sensory and pain measurement in humans. The equipment and techniques described are commonly found in pain clinics or are easy to...
21.6K
An Experimental Paradigm for the Prediction of Post-Operative Pain (PPOP)14:56

An Experimental Paradigm for the Prediction of Post-Operative Pain (PPOP)

21.9K
Diffuse noxious inhibitory control, temporal summation and wound hyperalgesia testing are demonstrated in the obstetric patient. These tests evaluate inhibitory and excitatory mechanisms of pain processing and are here utilized to evaluate endogenous analgesia at different time-points during pregnancy and the peripartum period to help reveal individual s risk for persistent...
21.9K
Experimental Generation of Carcinoma-Associated Fibroblasts (CAFs) from Human Mammary Fibroblasts15:43

Experimental Generation of Carcinoma-Associated Fibroblasts (CAFs) from Human Mammary Fibroblasts

24.0K
Carcinoma-associated fibroblasts (CAFs) rich in myofibroblasts present within the tumour stroma, play a major role in driving tumour progression. We developed a coimplantation tumour xengraft model for experimentally generating CAFs from human mammary fibroblasts. The protocol describes how to establish CAF myofibroblasts that acquire an ability to promote...
24.0K
Correlation of Experimental Data01:23

Correlation of Experimental Data

480
Dimensional analysis simplifies complex physical problems and guides experimental investigations, but it does not provide complete solutions. It identifies the dimensionless groups that influence a phenomenon, but experimental data is needed to establish the specific relationships and validate theoretical predictions.
For example, a spherical particle moving through a viscous fluid experiences drag. Dimensional analysis shows that the drag force depends on the particle's diameter, velocity,...
480
Design Example: Setting a Curve Using Design Data01:09

Design Example: Setting a Curve Using Design Data

229
Designing and plotting a curve using field data requires precise calculations and execution. A horizontal curve with a radius of 200 meters and an intersection angle of 20 degrees is established using the method of perpendicular offsets from the long chord. The long chord, which spans between the curve's endpoints, is calculated to be 69.46 meters in length. To maintain accuracy in plotting, intervals of 3 meters are selected along the chord.The engineer determines the offset distances for each...
229

You might also read

Related Articles

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

Sort by
Same author

Inhaled Levodopa for the Management of OFF Episodes in Patients with Parkinson's Disease: A Network Meta-analysis.

Neurology and therapy·2026
Same author

TRPC5 as a modulator of TRPV1 signalling in pathological pain states.

Neuropharmacology·2026
Same author

Selective neuronal restoration of progranulin does not prevent the frontotemporal dementia like-phenotype of progranulin knockout mice.

Journal of neuroinflammation·2026
Same author

Modest improvement of metabolic and behavioral deficits with long-term ambroxol treatment in a Pink1<sup>-/-</sup>SNCA<sup>A53T</sup> double mutant mouse model of Parkinson's disease.

Acta pharmacologica Sinica·2025
Same author

Schmerz (Berlin, Germany)·2025
Same author

In memory of Professor Dr. med. Dr. h. c. Kay Brune (1941-2025), Past President of the German Society for Experimental and Clinical Pharmacology and Toxicology and honorary member of the German Society for Pharmacology.

Naunyn-Schmiedeberg's archives of pharmacology·2025

Related Experiment Video

Updated: Jan 20, 2026

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data
12:08

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

Published on: August 13, 2014

25.0K

[Generating knowledge from complex data sets in human experimental pain research].

Jörn Lötsch1,2, Gerd Geisslinger3,4, Carmen Walter4

  • 1Institut für Klinische Pharmakologie, Goethe-Universität, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Deutschland. j.loetsch@em.uni-frankfurt.de.

Schmerz (Berlin, Germany)
|September 4, 2019
PubMed
Summary
This summary is machine-generated.

Data science and machine learning are revolutionizing pain research by uncovering complex patterns in large datasets. These advanced methods aid in understanding pain phenotypes and discovering novel analgesic drugs.

Keywords:
Clinicak pharmakologyData scienceHuman experimental pain researchMachine-learningPharmacometrics

More Related Videos

A Protocol of Manual Tests to Measure Sensation and Pain in Humans
07:28

A Protocol of Manual Tests to Measure Sensation and Pain in Humans

Published on: December 19, 2016

21.6K
An Experimental Paradigm for the Prediction of Post-Operative Pain PPOP
14:56

An Experimental Paradigm for the Prediction of Post-Operative Pain PPOP

Published on: January 27, 2010

21.9K

Related Experiment Videos

Last Updated: Jan 20, 2026

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data
12:08

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

Published on: August 13, 2014

25.0K
A Protocol of Manual Tests to Measure Sensation and Pain in Humans
07:28

A Protocol of Manual Tests to Measure Sensation and Pain in Humans

Published on: December 19, 2016

21.6K
An Experimental Paradigm for the Prediction of Post-Operative Pain PPOP
14:56

An Experimental Paradigm for the Prediction of Post-Operative Pain PPOP

Published on: January 27, 2010

21.9K

Area of Science:

  • Data science applications in biomedical research
  • Computational approaches to pain management
  • Machine learning in clinical research

Background:

  • Pain exhibits complex pathophysiology and diverse clinical presentations, generating substantial research data.
  • Traditional statistical methods are often insufficient for analyzing high-dimensional pain research data.
  • Big data analytics offers new avenues for understanding pain mechanisms and developing treatments.

Purpose of the Study:

  • To provide an overview of contemporary data science methods in pain research.
  • To highlight the application of machine learning in analyzing complex pain data.
  • To illustrate how data-driven approaches can accelerate the discovery of new analgesics.

Main Methods:

  • Analysis of large datasets from functional magnetic resonance imaging and genetic sequencing.
  • Application of machine learning algorithms for pattern detection and classification.
  • Utilizing electronic knowledge bases for hypothesis generation and drug discovery.

Main Results:

  • Machine learning effectively identifies meaningful structures in high-dimensional pain data.
  • Predictive models can be developed to classify clinical pain phenotypes.
  • Data-driven approaches facilitate the discovery and repositioning of analgesic drugs.

Conclusions:

  • Data science, particularly machine learning, is crucial for advancing pain research.
  • The integration of data analytics enables a deeper understanding of pain and accelerates therapeutic development.
  • The data-information-knowledge-wisdom (DIKW) framework guides the effective use of big data in pain science.