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

Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

6.4K
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...
6.4K
Applications of Molecular Taxonomy01:20

Applications of Molecular Taxonomy

162
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...
162
Modern Molecular Taxonomy01:29

Modern Molecular Taxonomy

218
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...
218
Phylogenetic Trees03:21

Phylogenetic Trees

47.9K
Phylogenetic trees come in many forms. It matters in which sequence the organisms are arranged from the bottom to the top of the tree, but the branches can rotate at their nodes without altering the information. The lines connecting individual nodes can be straight, angled, or even curved.
47.9K
Phylogeny01:23

Phylogeny

53.5K
Phylogeny is concerned with the evolutionary diversification of organisms or groups of organisms. A group of organisms with a name is called a taxon (singular). Taxa (plural) can span different levels of the evolutionary hierarchy. For instance, the group containing all birds is a taxon (comprising the class Aves), and the group of all species of daisies (the genus Bellis) is a taxon. Phylogenies can likewise include just one genus (i.e., depict species relationships) or span an entire kingdom.
53.5K
Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

7.5K
The genomes of eukaryotes are punctuated by long stretches of sequence which do not code for proteins or RNAs. Although some of these regions do contain crucial regulatory sequences, the vast majority of this DNA serves no known function. Typically, these regions of the genome are the ones in which the fastest change, in evolutionary terms, is observed, because there is typically little to no selection pressure acting on these regions to preserve their sequences.
In contrast, regions which code...
7.5K

You might also read

Related Articles

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

Sort by
Same author

The genetic foundations of convergent traits.

Nature reviews. Genetics·2026
Same author

An Evolutionary Metric for Estimating PhyloAges from Bulk Sequencing of Hematopoietic Stem Cells Reveals the Tempo of Blood Aging in Cancer and Longevity.

Journal of molecular evolution·2025
Same author

Robust and Efficient Confidence Limits for Phylogenomic Inference of Organismal Relationships.

Molecular biology and evolution·2025
Same author

MEGA 12.1: Cross-Platform Release for macOS and Linux Operating Systems.

Journal of molecular evolution·2025
Same author

MyESL: A Software for Evolutionary Sparse Learning in Molecular Phylogenetics and Genomics.

Molecular biology and evolution·2025
Same author

MEGA-GPT: Artificial Intelligence Guidance and Building Analytical Protocols Using MEGA Software.

Molecular biology and evolution·2025
Same journal

Population Epigenetics: Deciphering DNA Methylation Diversity and its Implications for Health, Disease, and Evolution.

Molecular biology and evolution·2026
Same journal

Genomic signature of repeated transitions to diurnality in spiders.

Molecular biology and evolution·2026
Same journal

Phylogenomic blind spots: The limits of UCE and BUSCO loci in the presence of gene flow.

Molecular biology and evolution·2026
Same journal

seqLens: Optimizing Language Models for Genomic Predictions.

Molecular biology and evolution·2026
Same journal

The transcriptional and translational outcomes for pseudogenes in bacterial endosymbionts.

Molecular biology and evolution·2026
Same journal

800 million years of co-evolution in the green plant lineage - the case of LEUNIG and SEUSS transcriptional co-regulators.

Molecular biology and evolution·2026
See all related articles

Related Experiment Video

Updated: Oct 1, 2025

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
08:57

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

16.1K

Embracing Green Computing in Molecular Phylogenetics.

Sudhir Kumar1,2

  • 1Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA, USA.

Molecular Biology and Evolution
|March 4, 2022
PubMed
Summary
This summary is machine-generated.

Phylogenomics research generates a large carbon footprint. Innovative green computing methods can reduce environmental impact and improve scientific rigor for big data analyses.

Keywords:
carbon footprintgreen computingmolecular evolutionphylogenetics

More Related Videos

A Practical Guide to Phylogenetics for Nonexperts
12:00

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

35.5K
A Concoction Pipeline for Generating Molecular Operational Taxonomic Units (MOTUs) Among Riparian and Aquatic Beetles
10:23

A Concoction Pipeline for Generating Molecular Operational Taxonomic Units (MOTUs) Among Riparian and Aquatic Beetles

Published on: July 11, 2025

270

Related Experiment Videos

Last Updated: Oct 1, 2025

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
08:57

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

16.1K
A Practical Guide to Phylogenetics for Nonexperts
12:00

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

35.5K
A Concoction Pipeline for Generating Molecular Operational Taxonomic Units (MOTUs) Among Riparian and Aquatic Beetles
10:23

A Concoction Pipeline for Generating Molecular Operational Taxonomic Units (MOTUs) Among Riparian and Aquatic Beetles

Published on: July 11, 2025

270

Area of Science:

  • Evolutionary biology
  • Computational biology
  • Environmental science

Background:

  • Molecular evolutionary analyses involve computationally intensive processes like sequence alignment and phylogenetic tree inference.
  • The increasing scale of genomic data in phylogenomics contributes significantly to the environment's carbon footprint through energy consumption and electronic waste.
  • Addressing the environmental impact of computational biology is crucial for sustainable scientific practices.

Purpose of the Study:

  • To highlight the environmental consequences of large-scale phylogenomic analyses.
  • To introduce the concept of green computing as a solution to mitigate the carbon footprint of evolutionary research.
  • To emphasize the potential for greener computational methods to enhance scientific rigor and accessibility.

Main Methods:

  • Review of computationally intensive steps in molecular evolutionary analyses.
  • Discussion of the environmental impact of large genomic datasets and high-performance computing.
  • Exploration of innovative methods and heuristics for reducing computational costs.

Main Results:

  • Phylogenomic analyses, essential for understanding molecular evolution, have a substantial carbon footprint.
  • Green computing strategies offer viable solutions to reduce energy usage and electronic waste in evolutionary research.
  • Adopting greener computational approaches can lead to more sustainable and inclusive big data analytics.

Conclusions:

  • Reducing the carbon footprint of phylogenomics is an urgent environmental and scientific challenge.
  • Innovative and greener computational methods are key to sustainable big data research in evolutionary biology.
  • The adoption of green computing practices will foster greater scientific rigor and broader participation in computational biology.