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

Imaging Biological Samples with Optical Microscopy01:18

Imaging Biological Samples with Optical Microscopy

11.9K
Optical microscopy uses optic principles to provide detailed images of samples. Antonie van Leeuwenhoek designed the first compound optical microscope in the 17th century to visualize blood cells, bacteria, and yeast cells. In 1830, Joseph Jackson Lister created an essentially modern light microscope. The 20th century saw the development of microscopes with enhanced magnification and resolution.
In optical microscopy, the specimen to be viewed is placed on a glass slide and clipped on the stage...
11.9K
GIS Software, Hardware, and Sources of GIS Data01:23

GIS Software, Hardware, and Sources of GIS Data

898
A Geographic Information System (GIS) combines specialized software and hardware to effectively manage, analyze, and present spatial and related data. GIS software includes critical functionalities such as a user interface for easy navigation, database management tools for handling spatial and attribute data, and data retrieval features for efficient access. Analytical tools transform raw data into insights, while display functions produce maps and reports in various formats for effective...
898

You might also read

Related Articles

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

Sort by
Same author

Multifocal cohort analysis unveils cell types associated with regional lymph node seeding in prostate cancer.

Genome medicine·2026
Same author

Run-length compressed metagenomic read classification with SMEM-finding and tagging.

iScience·2026
Same author

Columba: fast approximate pattern matching with optimized search schemes.

Bioinformatics (Oxford, England)·2025
Same author

Sex-specific recombination landscape in a species with holocentric chromosomes.

Genetics·2025
Same author

Generating random graphs with prescribed graphlet frequency bounds derived from probabilistic networks.

PloS one·2025
Same author

Soma-localized Rab39 inhibits synaptic autophagy by controlling trafficking of Atg9 vesicles.

The EMBO journal·2025
Same journal

conMItion: an R package adjusting confounding factors for associations in multi-omics.

Bioinformatics (Oxford, England)·2026
Same journal

SpaMFG: a Spatial Multi-omics Integration Method based on Feature Grouping.

Bioinformatics (Oxford, England)·2026
Same journal

CSCN: Inference of Cell-Specific Causal Networks Using Single-Cell RNA-Seq Data.

Bioinformatics (Oxford, England)·2026
Same journal

Sparse CCA-Based Mediation Analysis with High-Dimensional Exposures and Mediators.

Bioinformatics (Oxford, England)·2026
Same journal

Enhancing Cross-Context Generalization in Drug Perturbation Prediction with a Multimodal Conditional Diffusion Framework.

Bioinformatics (Oxford, England)·2026
Same journal

Primer Design through Submodular Function Estimation.

Bioinformatics (Oxford, England)·2026
See all related articles

Related Experiment Video

Updated: Mar 3, 2026

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

10.1K

OMSim: a simulator for optical map data.

Giles Miclotte1,2, Stéphane Plaisance3, Stephane Rombauts2,4,5

  • 1Department of Information Technology, IDLab, Ghent University-IMEC, Ghent 9052, Belgium.

Bioinformatics (Oxford, England)
|May 5, 2017
PubMed
Summary
This summary is machine-generated.

A new simulator, OMSim, generates synthetic optical map data for Bionano Genomics. This tool aids in developing and benchmarking genome analysis software and optimizing experimental setups for large genomes.

More Related Videos

Multimodal Volumetric Retinal Imaging by Oblique Scanning Laser Ophthalmoscopy oSLO and Optical Coherence Tomography OCT
12:22

Multimodal Volumetric Retinal Imaging by Oblique Scanning Laser Ophthalmoscopy oSLO and Optical Coherence Tomography OCT

Published on: August 4, 2018

9.0K
Two-photon Calcium Imaging in Mice Navigating a Virtual Reality Environment
08:12

Two-photon Calcium Imaging in Mice Navigating a Virtual Reality Environment

Published on: February 20, 2014

32.4K

Related Experiment Videos

Last Updated: Mar 3, 2026

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

10.1K
Multimodal Volumetric Retinal Imaging by Oblique Scanning Laser Ophthalmoscopy oSLO and Optical Coherence Tomography OCT
12:22

Multimodal Volumetric Retinal Imaging by Oblique Scanning Laser Ophthalmoscopy oSLO and Optical Coherence Tomography OCT

Published on: August 4, 2018

9.0K
Two-photon Calcium Imaging in Mice Navigating a Virtual Reality Environment
08:12

Two-photon Calcium Imaging in Mice Navigating a Virtual Reality Environment

Published on: February 20, 2014

32.4K

Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Bionano Genomics platform enables optical detection of sequence patterns in long DNA molecules (up to 2.5 Mbp).
  • Optical maps aid in validating genome assemblies and detecting structural variations.
  • Simulated optical map data is crucial for developing and benchmarking analysis tools.

Purpose of the Study:

  • To develop a simulator for generating synthetic optical map data.
  • To provide a tool for developing and benchmarking genome analysis software.
  • To optimize experimental setups for optical genome mapping.

Main Methods:

  • Development of OMSim, a Python-based simulation tool.
  • Creation of a cross-platform graphical user interface.
  • Testing compatibility with Bionano Genomics Irys software and scaffolding scripts.

Main Results:

  • OMSim generates synthetic optical map data mimicking real Bionano Genomics data.
  • The simulator is compatible with existing Bionano Genomics software.
  • OMSim handles large genomes (>30 Gbp) with high throughput and low memory usage.

Conclusions:

  • OMSim provides a valuable resource for the Bionano Genomics community.
  • The availability of OMSim will accelerate the development of optical mapping analysis tools.
  • This simulator facilitates the optimization of experimental designs for various genomes.