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

Genomics02:02

Genomics

39.8K
Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
39.8K
Genomic Imprinting and Inheritance02:30

Genomic Imprinting and Inheritance

36.9K
Diploid organisms inherit genetic material through chromosomes from both parents. Copies of the same gene are known as alleles. In most cases, both alleles are simultaneously expressed and allow various cellular processes to function optimally. If one of the alleles is missing or mutated, the expression of the other allele can compensate; however, this is not true for all genes.
The expression of some genes depends on which parent passed the gene to the offspring, through a phenomenon known as...
36.9K
Genome Size and the Evolution of New Genes03:21

Genome Size and the Evolution of New Genes

9.0K
While every living organism has a genome of some kind (be it RNA, or DNA), there is considerable variation in the sizes of these blueprints. One major factor that impacts genome size is whether the organism is prokaryotic or eukaryotic. In prokaryotes, the genome contains little to no non-coding sequence, such that genes are tightly clustered in groups or operons sequentially along the chromosome. Conversely, the genes in eukaryotes are punctuated by long stretches of non-coding sequence.
9.0K
Drug Distribution: Volume of Distribution01:25

Drug Distribution: Volume of Distribution

7.3K
The volume of distribution refers to the theoretical volume necessary to contain the entire amount of an administered drug at the same concentration observed in the blood plasma. The body's intracellular fluid compartment, which makes up two-thirds of the total body water, is contrasted with the extracellular fluid compartment—comprising plasma and interstitial fluid—that accounts for one-third. The volume of distribution can vary depending on the characteristics of the drug.
7.3K
F Distribution01:19

F Distribution

9.0K
The F distribution was named after Sir Ronald Fisher, an English statistician. The F statistic is a ratio (a fraction) with two sets of degrees of freedom; one for the numerator and one for the denominator. The F distribution is derived from the Student's t distribution. The values of the F distribution are squares of the corresponding values of the t distribution. One-Way ANOVA expands the t test for comparing more than two groups. The scope of that derivation is beyond the level of this...
9.0K
Comparing Mitochondrial, Chloroplast, and Prokaryotic Genomes02:16

Comparing Mitochondrial, Chloroplast, and Prokaryotic Genomes

15.4K
The present-day mitochondrial and chloroplast genomes have retained some of the characteristics of their ancestral prokaryotes and also have acquired new attributes during their evolution within eukaryotic cells. Like prokaryotic genomes, mitochondrial and chloroplast genomes neither bind with histone-like proteins nor show complex packaging into chromosome-like structures, as observed in eukaryotes. Unlike mitotic cell divisions observed in eukaryotic cells, mitochondria and chloroplasts...
15.4K

You might also read

Related Articles

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

Sort by
Same author

EpiATLAS - a reference for human epigenomic research.

bioRxiv : the preprint server for biology·2026
Same author

Transposable elements impact the human regulatory landscape through cell type specific epigenomic associations.

Nature communications·2026
Same author

Distinct associations among human milk microbiota and minerals in relation to early infant growth: a longitudinal study.

Journal of translational medicine·2026
Same author

Diagnostic performance of eosinopenia for identifying bacterial infections in the emergency department: a prospective multicenter study.

BMC emergency medicine·2026
Same author

Benchmarking of sequencing technologies defines optimal strategies for genetic variants detection in a human genome.

Genome biology·2026
Same author

Human milk microbial species are associated with mild growth deficits during early infancy among Guatemalan mother-infant dyads.

Frontiers in microbiomes·2026
Same journal

A comprehensive reference genome assembly dataset of birds inhabiting Denmark, Greenland, and the Faroe Islands.

GigaScience·2026
Same journal

NanoporeDB: A Structural Resource Of Multimeric Protein Nanopores For Single-Molecule Sensing.

GigaScience·2026
Same journal

From the Brain Cell Atlas to Precision Neurology: A review of the application of AI-driven multi-omics in brain science.

GigaScience·2026
Same journal

Comparison of Deep Learning Approaches for Extreme Low-SNR Image Restoration.

GigaScience·2026
Same journal

ScopeViewer: A Browser-Based Solution for Visualizing Large Biological Images.

GigaScience·2026
Same journal

ChatMDV: Reducing Technical Barriers in Bioinformatics Analysis using Large Language Models.

GigaScience·2026
See all related articles

Related Experiment Video

Updated: Jan 23, 2026

Author Spotlight: Advancing Biotherapeutic Mass Calculation by Introducing mAbScale, a Python-Based Desktop Application
04:24

Author Spotlight: Advancing Biotherapeutic Mass Calculation by Introducing mAbScale, a Python-Based Desktop Application

Published on: June 16, 2023

2.3K

GenPipes: an open-source framework for distributed and scalable genomic analyses.

Mathieu Bourgey1,2, Rola Dali1,2, Robert Eveleigh1,2

  • 1Canadian Centre for Computational Genomics, Montréal, QC, Canada.

Gigascience
|June 12, 2019
PubMed
Summary
This summary is machine-generated.

GenPipes is a flexible Python framework for genomics research, simplifying the analysis of diverse data types. This bioinformatics software supports high-performance computing and cloud deployment for efficient large-scale data processing.

Keywords:
bioinformaticsframeworksgenomicspipelineworkflowworkflow management systems

More Related Videos

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
08:03

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

2.7K
Watershed Planning within a Quantitative Scenario Analysis Framework
12:44

Watershed Planning within a Quantitative Scenario Analysis Framework

Published on: July 24, 2016

8.5K

Related Experiment Videos

Last Updated: Jan 23, 2026

Author Spotlight: Advancing Biotherapeutic Mass Calculation by Introducing mAbScale, a Python-Based Desktop Application
04:24

Author Spotlight: Advancing Biotherapeutic Mass Calculation by Introducing mAbScale, a Python-Based Desktop Application

Published on: June 16, 2023

2.3K
Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
08:03

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

2.7K
Watershed Planning within a Quantitative Scenario Analysis Framework
12:44

Watershed Planning within a Quantitative Scenario Analysis Framework

Published on: July 24, 2016

8.5K

Area of Science:

  • Bioinformatics
  • Genomics
  • Computational Biology

Background:

  • The decreasing cost of DNA sequencing and advancements in genomics technologies necessitate efficient bioinformatics software for large-scale data processing.
  • There is a growing need for validated, scalable bioinformatics tools to handle the increasing volume and complexity of genomic data.

Purpose of the Study:

  • To introduce GenPipes, a flexible Python-based framework for developing and deploying multi-step bioinformatics workflows.
  • To provide a solution for efficient, large-scale genomics data analysis on high-performance computing clusters and cloud platforms.

Main Methods:

  • GenPipes is a Python framework designed for creating and deploying multi-step bioinformatics workflows.
  • The framework is optimized for high-performance computing (HPC) clusters and cloud environments.
  • It supports various genomics applications including RNA sequencing, DNA sequencing, and metagenomics.

Main Results:

  • GenPipes implements 12 validated and scalable pipelines for diverse genomics applications.
  • The software is open-source (GPLv3), continuously updated, and available via a Docker image for easy installation.
  • The framework has been successfully configured on multiple servers, demonstrating its practical applicability.

Conclusions:

  • GenPipes provides genomics researchers with a user-friendly method for analyzing various data types.
  • The framework is customizable to specific research needs and computational resources.
  • It offers flexibility for researchers to develop their own custom bioinformatics workflows.