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

Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

17.1K
Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
17.1K
Multiple Allele Traits01:49

Multiple Allele Traits

33.9K
The Concept of Multiple Allelism
33.9K
Cell Specific Gene Expression01:58

Cell Specific Gene Expression

13.4K
Multicellular organisms contain a variety of structurally and functionally distinct cell types, but the DNA in all the cells originated from the same parent cells. The differences in the cells can be attributed to the differential gene expression. Liver cells, whose functions include detoxification of blood, production of bile to metabolize fats, and synthesis of proteins essential for metabolism, must express a specific set of genes to perform their functions. Gene expression also varies with...
13.4K
Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

127
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
127
Single Nucleotide Polymorphisms-SNPs01:05

Single Nucleotide Polymorphisms-SNPs

13.9K
A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...
13.9K
Test for Homogeneity01:23

Test for Homogeneity

1.9K
The goodness–of–fit test can be used to decide whether a population fits a given distribution, but it will not suffice to decide whether two populations follow the same unknown distribution. A different test, called the test for homogeneity, can be used to conclude whether two populations have the same distribution. To calculate the test statistic for a test for homogeneity, follow the same procedure as with the test of independence. The hypotheses for the test for homogeneity can...
1.9K

You might also read

Related Articles

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

Sort by
Same author

Optimal transport fate mapping resolves T cell differentiation dynamics across tissues.

bioRxiv : the preprint server for biology·2026
Same author

MICRON learns outcome-associated representations of spatial immune microenvironments.

bioRxiv : the preprint server for biology·2026
Same author

Bridging Genomics and Clinical Medicine: RSVrecon Enhances RSV Surveillance With Automated Genotyping and Clinically Important Mutation Reporting.

Influenza and other respiratory viruses·2026
Same author

Peripheral immune patterns enable robust cross-platform prediction of ALS onset and progression.

bioRxiv : the preprint server for biology·2025
Same author

Single-cell transcriptomics yield insights into the stress-immune interplay and inform disease risk.

bioRxiv : the preprint server for biology·2025
Same author

Bridging Genomics and Clinical Medicine: RSVrecon Enhances RSV Surveillance with Automated Genotyping and Clinically Important Mutation Reporting.

bioRxiv : the preprint server for biology·2025

Related Experiment Video

Updated: May 28, 2025

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

15.6K

Conditional similarity triplets enable covariate-informed representations of single-cell data.

Chi-Jane Chen1, Haidong Yi2, Natalie Stanley3,4,5

  • 1Department of Computer Science, The University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA. chijane@cs.unc.edu.

BMC Bioinformatics
|February 9, 2025
PubMed
Summary

This study introduces CytoCoSet, a machine learning method that improves immune cell analysis by incorporating clinical data. This approach enhances the prediction of clinical outcomes for better diagnostics and treatments.

Keywords:
Clinical predictionDeep-learningImmune profilingSingle-cell

More Related Videos

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues
10:12

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

18.4K
A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations
09:34

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations

Published on: October 25, 2018

6.6K

Related Experiment Videos

Last Updated: May 28, 2025

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

15.6K
Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues
10:12

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

18.4K
A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations
09:34

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations

Published on: October 25, 2018

6.6K

Area of Science:

  • Computational Biology
  • Immunology
  • Machine Learning

Background:

  • Single-cell technologies provide detailed immune cell profiling.
  • Machine learning is used to create immunological summaries for diagnostics.
  • Current methods predict only one outcome, ignoring other clinical data.

Purpose of the Study:

  • To develop a novel machine learning approach for incorporating clinical covariates into immune signature analysis.
  • To create per-sample encodings that reflect both immune profiles and clinical information.

Main Methods:

  • Introduced CytoCoSet, a set-based encoding method.
  • Formulated a loss function with a triplet term to penalize disparate embeddings for similar covariates.
  • Optimized model parameters to integrate immune signatures and clinical data.

Main Results:

  • CytoCoSet effectively incorporates measured covariates into per-sample encodings.
  • The method learns featurizations that capture both immune and clinical information.
  • Optimized encodings improve the prediction of clinical outcomes.

Conclusions:

  • Integrating clinical covariates enhances the accuracy of per-sample encodings.
  • This approach leads to more robust predictions of clinical phenotypes.
  • The method has potential for improving diagnostic and treatment strategies.