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

Genome Annotation and Assembly03:36

Genome Annotation and Assembly

19.9K
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.
19.9K
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

6.6K
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...
6.6K
Next-generation Sequencing03:00

Next-generation Sequencing

96.0K
The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features....
96.0K
Genomics02:02

Genomics

38.8K
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...
38.8K
RNA-seq03:21

RNA-seq

11.1K
RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
11.1K
Improving Translational Accuracy02:07

Improving Translational Accuracy

12.7K
Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
12.7K

You might also read

Related Articles

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

Sort by
Same author

Improving metagenome binning by integrating intrinsic features and taxonomy.

Nature biotechnology·2026
Same author

Translational bioinformatics stalls at implementation.

Briefings in bioinformatics·2026
Same author

LLM-Assessed Relatedness of Microbiome Study Descriptions Aligns more Strongly with Functional than with Taxonomic Profile Similarity.

Microbial ecology·2026
Same author

Modeling nascent transcription from chromatin landscape and structure with CLASTER.

Genome biology·2026
Same author

The HUNT study identifies host genetic factors reproducibly associated with human gut microbiota composition.

Nature genetics·2026
Same author

Genome-wide association analyses highlight the role of the intestinal molecular environment in human gut microbiota variation.

Nature genetics·2026

Related Experiment Video

Updated: Nov 23, 2025

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.5K

Improved metagenome binning and assembly using deep variational autoencoders.

Jakob Nybo Nissen1,2, Joachim Johansen2, Rosa Lundbye Allesøe2

  • 1Department of Health Technology, Technical University of Denmark, Lyngby, Denmark.

Nature Biotechnology
|January 5, 2021
PubMed
Summary
This summary is machine-generated.

VAMB, a new deep learning tool, improves microbial species reconstruction from metagenomics data. It enhances genome recovery and strain separation, revealing geographical patterns in the human gut microbiome.

More Related Videos

A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data
09:34

A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data

Published on: September 25, 2021

4.3K
Hybrid De Novo Genome Assembly for the Generation of Complete Genomes of Urinary Bacteria using Short- and Long-read Sequencing Technologies
12:08

Hybrid De Novo Genome Assembly for the Generation of Complete Genomes of Urinary Bacteria using Short- and Long-read Sequencing Technologies

Published on: August 20, 2021

5.5K

Related Experiment Videos

Last Updated: Nov 23, 2025

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.5K
A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data
09:34

A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data

Published on: September 25, 2021

4.3K
Hybrid De Novo Genome Assembly for the Generation of Complete Genomes of Urinary Bacteria using Short- and Long-read Sequencing Technologies
12:08

Hybrid De Novo Genome Assembly for the Generation of Complete Genomes of Urinary Bacteria using Short- and Long-read Sequencing Technologies

Published on: August 20, 2021

5.5K

Area of Science:

  • Microbial genomics
  • Bioinformatics
  • Computational biology

Background:

  • Reconstructing microbial genomes from metagenomic data is crucial for understanding microbial communities.
  • Existing metagenomic binning tools face challenges in accurately assembling microbial genomes.
  • Integrating diverse data types, like sequence coabundance and k-mer distributions, can improve binning accuracy.

Purpose of the Study:

  • To develop a novel computational tool, Variational Autoencoders for Metagenomic Binning (VAMB), for improved microbial genome reconstruction.
  • To assess VAMB's performance against state-of-the-art binning methods using simulated and real-world metagenomic datasets.
  • To explore the utility of VAMB in resolving closely related microbial strains and analyzing large-scale microbiome population structures.

Main Methods:

  • Developed VAMB, a program utilizing deep variational autoencoders to integrate sequence coabundance and k-mer distribution data.
  • Employed unsupervised learning to cluster genomic data without prior knowledge of the dataset.
  • Benchmarked VAMB against existing binning tools on simulated datasets and a large cohort of 1,000 human gut microbiome samples.

Main Results:

  • VAMB significantly outperformed existing methods, reconstructing 29-98% more near-complete genomes from simulated data and 45% more from real data.
  • Successfully separated closely related microbial strains with up to 99.5% average nucleotide identity (ANI).
  • Resolved distinct clusters for Bacteroides vulgatus and Bacteroides dorei from 1,000 human gut samples and identified geographical distribution patterns for 2,606 near-complete bins.

Conclusions:

  • VAMB offers a powerful and accurate approach for microbial genome reconstruction from metagenomic data.
  • The tool's ability to integrate multiple data types and resolve fine-scale genomic variation advances the field of metagenomic binning.
  • VAMB facilitates large-scale microbiome population genomics, enabling discoveries such as geographical variations in gut microbial species.