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

Molecular Models02:00

Molecular Models

37.5K
Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.
37.5K
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

5.8K
Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
5.8K
Model Approaches for Pharmacokinetic Data: Compartment Models01:14

Model Approaches for Pharmacokinetic Data: Compartment Models

888
Compartmental analysis is a widely adopted approach to characterizing drug pharmacokinetics. It uses compartment models that conceptualize the body as a collection of reversibly communicating compartments, each representing a group of tissues exhibiting similar drug distribution characteristics. The movement rate of the drug between these compartments is typically described by first-order kinetics.
Two primary types of compartment models are recognized: mammillary and catenary. The more...
888
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

333
Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
333
Modern Molecular Taxonomy01:29

Modern Molecular Taxonomy

836
Advancements in molecular biology have revolutionized the identification and characterization of bacteria, with multiple methods leveraging DNA sequencing for enhanced precision. As sequencing technologies improve and costs decline, these approaches are increasingly used in clinical, environmental, and evolutionary studies.Multilocus Sequence Typing (MLST) examines several housekeeping genes, essential chromosomal genes encoding cellular functions, to distinguish strains. Approximately...
836
Applications of Molecular Taxonomy01:20

Applications of Molecular Taxonomy

705
Molecular taxonomy has revolutionized the understanding and classification of bacteria, providing precise insights into their diversity, evolutionary relationships, and ecological roles. By utilizing molecular techniques such as DNA sequencing and fingerprinting, researchers have made significant strides in various fields related to bacterial studies.Resolving Taxonomic AmbiguitiesMolecular taxonomy has been instrumental in distinguishing closely related bacterial species initially thought to...
705

You might also read

Related Articles

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

Sort by
Same author

FINDER converts zero-background kinetic fingerprinting into area-scalable attomolar biomarker detection.

bioRxiv : the preprint server for biology·2026
Same author

Npl4 decodes polyubiquitin length and gates D1-D2 coupling in human VCP/p97.

Research square·2026
Same author

Npl4 decodes polyubiquitin length and gates D1-D2 coupling in human VCP/p97.

bioRxiv : the preprint server for biology·2026
Same author

ASPL-driven subunit exchange remodels VCP/p97 hexamers and is impaired by a multisystem proteinopathy mutation.

bioRxiv : the preprint server for biology·2026
Same author

A leader-repeat hairpin blocks extraneous CRISPR RNA production in diverse CRISPR-Cas13 systems.

The EMBO journal·2026
Same author

Directional co-transcriptional folding and pausing create kinetic checkpoints for riboswitch-controlled gene expression.

bioRxiv : the preprint server for biology·2026
Same journal

Genetic Impacts on Variability of Body Fat Distribution Uncover Gene-Environment and Gene-Gene Interactions.

bioRxiv : the preprint server for biology·2026
Same journal

16S ribosomal RNA modification drives transcript-specific translation efficiency.

bioRxiv : the preprint server for biology·2026
Same journal

FlcE latches onto the FliL-stator complex to turbocharge flagellar motility in <i>Borrelia burgdorferi</i>.

bioRxiv : the preprint server for biology·2026
Same journal

Synaptic pruning, myelination and the emergence of psychiatric disorders in late adolescence.

bioRxiv : the preprint server for biology·2026
Same journal

Structural and functional insights into the Rcs phosphorelay.

bioRxiv : the preprint server for biology·2026
Same journal

The structural basis of RanGAP1 regulation and catalysis in nuclear transport.

bioRxiv : the preprint server for biology·2026
See all related articles

Related Experiment Video

Updated: May 3, 2026

Visualizing Single Molecular Complexes In Vivo Using Advanced Fluorescence Microscopy
11:26

Visualizing Single Molecular Complexes In Vivo Using Advanced Fluorescence Microscopy

Published on: September 8, 2009

9.3K

Foundation model for efficient biological discovery in single-molecule data.

Jieming Li1, Leyou Zhang2, Alexander Johnson-Buck3

  • 1Bristol Myers Squibb, New Brunswick, NJ, USA.

Biorxiv : the Preprint Server for Biology
|September 10, 2024
PubMed
Summary
This summary is machine-generated.

We developed META-SiM, a powerful AI tool that analyzes complex single-molecule fluorescence microscopy (SMFM) data. This approach accelerates biological discovery by identifying rare cellular events and previously unobserved biological states.

More Related Videos

High Precision FRET at Single-molecule Level for Biomolecule Structure Determination
11:24

High Precision FRET at Single-molecule Level for Biomolecule Structure Determination

Published on: May 13, 2017

10.7K
An In Vitro Single-Molecule Imaging Assay for the Analysis of Cap-Dependent Translation Kinetics
09:52

An In Vitro Single-Molecule Imaging Assay for the Analysis of Cap-Dependent Translation Kinetics

Published on: September 15, 2020

3.1K

Related Experiment Videos

Last Updated: May 3, 2026

Visualizing Single Molecular Complexes In Vivo Using Advanced Fluorescence Microscopy
11:26

Visualizing Single Molecular Complexes In Vivo Using Advanced Fluorescence Microscopy

Published on: September 8, 2009

9.3K
High Precision FRET at Single-molecule Level for Biomolecule Structure Determination
11:24

High Precision FRET at Single-molecule Level for Biomolecule Structure Determination

Published on: May 13, 2017

10.7K
An In Vitro Single-Molecule Imaging Assay for the Analysis of Cap-Dependent Translation Kinetics
09:52

An In Vitro Single-Molecule Imaging Assay for the Analysis of Cap-Dependent Translation Kinetics

Published on: September 15, 2020

3.1K

Area of Science:

  • Biophysics
  • Computational Biology
  • Molecular Biology

Background:

  • Data-intensive biological techniques offer deep insights but increase complexity.
  • Analyzing single-molecule fluorescence microscopy (SMFM) data often requires manual, iterative methods.
  • Discovering rare intermediates in SMFM data is challenging to systematize.

Purpose of the Study:

  • To introduce META-SiM, a foundation model for systematic and efficient SMFM data analysis.
  • To enable objective and accelerated discovery from complex single-molecule data.
  • To develop tools for visualization, comparison, and identification of condition-specific behaviors.

Main Methods:

  • Developed META-SiM, a transformer-based foundation model trained on diverse SMFM analysis tasks.
  • Utilized high-dimensional embedding vectors and the META-SiM Projector for data visualization and analysis.
  • Integrated Local Shannon Entropy for identifying subtle, condition-specific behaviors.

Main Results:

  • META-SiM achieved high performance across various SMFM analysis tasks, including trace selection, classification, and segmentation.
  • The META-SiM Projector facilitates efficient dataset visualization, labeling, comparison, and sharing.
  • Application to a single-molecule Förster resonance energy transfer (smFRET) dataset revealed a novel intermediate state in pre-mRNA splicing.

Conclusions:

  • META-SiM streamlines the analysis of complex single-molecule data, removing bottlenecks and improving objectivity.
  • The model systematizes and accelerates biological discovery from SMFM datasets.
  • META-SiM facilitates the identification of rare or subtle biological phenomena, advancing molecular biology research.