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

Language01:16

Language

921
Language is a unique communication system that uses words and systematic rules to organize and transmit information. Unlike other forms of communication, which may involve postures, movements, odors, or vocalizations, language relies on symbols and grammar. This makes human communication distinct from that of other species, who also communicate but do not use language in the same way humans do.
Corballis and Suddendorf (2007) and Tomasello and Rakoczy (2003) highlight the role of language in...
921
Genome Annotation and Assembly03:36

Genome Annotation and Assembly

21.1K
The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.
21.1K
Components of Language01:24

Components of Language

830
Language, whether spoken, signed, or written, consists of specific components: lexicon and grammar. The lexicon is the vocabulary of a language, comprising its words. Grammar is the set of rules used to convey meaning through the lexicon. For example, English grammar adds “-ed” to most verbs to indicate past tense. Words are formed by combining phonemes, which are the basic sound units of a language. Different languages have different sets of phonemes (e.g., “ah” vs.
830
Language Development01:22

Language Development

936
Children master language quickly and with relative ease, supported by both biological predisposition and reinforcement. B. F. Skinner (1957) proposed that language is learned through reinforcement, while Noam Chomsky (1965) argued that language acquisition mechanisms are biologically determined.
The critical period for language acquisition suggests that the ability to acquire language is at its peak early in life. As people age, this proficiency decreases. Language development begins very...
936
Language and Cognition01:27

Language and Cognition

812
Language serves as a bridge between ideas and communication, influencing how individuals perceive and interact with the world. Psychologists have long debated whether language shapes thought or vice versa. This discussion gained grip with Edward Sapir and Benjamin Lee Whorf in the 1940s, who proposed that language determines thought, a concept known as linguistic determinism. They suggested that the vocabulary and structure of a language influence how its speakers think and perceive reality.
812
T Cell Types and Functions01:24

T Cell Types and Functions

2.6K
When T cells with CD4 markers are activated, they give rise to two types of effector cells: helper T cells and regulatory T cells. Meanwhile, T cells with CD8 markers differentiate into effector cytotoxic T cells. The differentiation of CD4 T cells into helper T cell subsets, such as Th1, Th2, and Th17 cells, is dependent on the antigen type, antigen-presenting cell, and regulatory cytokines.
Th1 cells stimulate dendritic cells to express necessary co-stimulatory molecules on their surfaces for...
2.6K

You might also read

Related Articles

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

Sort by
Same author

Green Tea Consumption and Risk of All-Cause Mortality: Findings from a Prospective Cohort Study.

Nutrients·2026
Same author

First-Line Alectinib Versus Ceritinib With or Without Brain Radiotherapy in ALK-Positive Non-Small Cell Lung Cancer with Brain Metastases: A Real-World Multicenter Study from Vietnam.

Thoracic cancer·2026
Same author

A Versatile Multiplexed Immunofluorescence Strategy for Efficient, Host-Independent, and Scalable Spatial Protein Profiling.

Small methods·2026
Same author

Exploring the mechanisms of biofield therapy through joint electrophysiological recordings in humans and mice.

IBRO neuroscience reports·2026
Same author

Multidimensional Predictors of Tirzepatide Efficacy: Clinical, Genetic, and Molecular Biomarkers for Glycemic, Weight, and Organ Protection.

Pharmaceuticals (Basel, Switzerland)·2026
Same author

Pancreatic cyst epidemiology defined by endoscopic ultrasound: A single-center longitudinal study.

Pancreatology : official journal of the International Association of Pancreatology (IAP) ... [et al.]·2026
Same journal

Region-aware bridge modeling enables interpretable mesoscale representation of spatial transcriptomic tissue sections.

Bioinformatics advances·2026
Same journal

Microbiome differential abundance methodologies to detect relevant taxa associated with chemotherapy toxicity rate in colorectal cancer.

Bioinformatics advances·2026
Same journal

maldipickr dereplicates microbial MALDI-TOF spectra to facilitate multiplexed isolation.

Bioinformatics advances·2026
Same journal

RAM-MSA: an anytime memory-bounded method for exact multiple sequence alignment using path finding.

Bioinformatics advances·2026
Same journal

Interpretable machine learning for low-sample multi-omics: a case study of ferret vaccine response.

Bioinformatics advances·2026
Same journal

DeepTaxa: a hybrid CNN-BERT framework for 16S rRNA taxonomic classification.

Bioinformatics advances·2026
See all related articles

Related Experiment Video

Updated: Feb 12, 2026

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

1.2K

Cell type annotation using large language models (LLMs) and CytoAnalyst.

Khoi Nguyen1, Duy Tran2, Phuong Nguyen2

  • 1Department of Industrial and Systems Engineering, Wayne State University, Detroit, MI 48201, United States.

Bioinformatics Advances
|February 11, 2026
PubMed
Summary
This summary is machine-generated.

We developed CytoAnalyst, a semi-automatic cell type annotation tool using large language models (LLMs). This platform reduces manual effort in single-cell data analysis while ensuring biological accuracy.

More Related Videos

Involving Individuals with Developmental Language Disorder and Their Parents/Carers in Research Priority Setting
06:16

Involving Individuals with Developmental Language Disorder and Their Parents/Carers in Research Priority Setting

Published on: June 6, 2020

4.6K
Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language
09:27

Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language

Published on: October 13, 2018

10.8K

Related Experiment Videos

Last Updated: Feb 12, 2026

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

1.2K
Involving Individuals with Developmental Language Disorder and Their Parents/Carers in Research Priority Setting
06:16

Involving Individuals with Developmental Language Disorder and Their Parents/Carers in Research Priority Setting

Published on: June 6, 2020

4.6K
Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language
09:27

Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language

Published on: October 13, 2018

10.8K

Area of Science:

  • Computational Biology
  • Bioinformatics
  • Genomics

Background:

  • Cell annotation is crucial for interpreting single-cell data, but it is labor-intensive and requires specialized expertise.
  • Current methods face challenges in reproducibility and consistency due to manual curation and diverse bioinformatics tools.

Purpose of the Study:

  • To introduce CytoAnalyst, a novel semi-automatic cell type annotation platform.
  • To leverage large language models (LLMs) for efficient and accurate cell annotation in single-cell analysis.
  • To reduce the manual workload for researchers while maintaining biological integrity.

Main Methods:

  • Single-cell data undergoes dimension reduction, clustering, and differential analysis to identify cell groups and markers.
  • Meta's Llama and structured prompting are employed for inferring cell types.
  • Ontology, tissue context, and marker gene signatures enforce biological accuracy.

Main Results:

  • CytoAnalyst significantly reduces manual labor in cell annotation.
  • The platform maintains high biological accuracy through enforced constraints.
  • It offers a comprehensive suite of single-cell analysis tools, including quality control, clustering, and trajectory inference.

Conclusions:

  • CytoAnalyst provides a powerful, user-friendly solution for semi-automatic cell type annotation.
  • The integration of LLMs enhances efficiency and accuracy in single-cell data interpretation.
  • CytoAnalyst is freely accessible, promoting broader adoption and reproducibility in the field.