Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Evolutionary Relationships through Genome Comparisons

Evolutionary Relationships through Genome Comparisons

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...

Genomic DNA in Eukaryotes

Genomic DNA in Eukaryotes

Eukaryotes have large genomes compared to prokaryotes. To fit their genomes into a cell, eukaryotic DNA is packaged extraordinarily tightly inside the nucleus. To achieve this, DNA is tightly wound around proteins called histones, which are packaged into nucleosomes that are joined by linker DNA and coil into chromatin fibers. Additional fibrous proteins further compact the chromatin, which is recognizable as chromosomes during certain phases of cell division.

You might also read

Related Articles

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

Sort by

Same author

Interacting Species Database (ISDB): comprehensive resource for interspecies interactions at the molecular level.

Bioinformatics (Oxford, England)·2026

Same author

Sphingosine kinase-2 inhibition promotes immunogenic differentiation of myeloid-derived suppressor cells through an Acetyl-CoA carboxylase-phosphatidylcholine axis.

Nature communications·2026

Same author

S1P-S1PR1 signaling impairs CD8<sup>+</sup> T cell metabolism and effector function in tumors.

EMBO reports·2026

Same author

Displacement-Optimized Tanglegrams for Trees and Networks.

Molecular biology and evolution·2026

Same author

MMonitor for real-time monitoring of microbial communities using long reads.

Cell reports methods·2025

Same author

Enhanced ELL Phase Separation Is Crucial for Efficient DNA Damage Repair to Restart Transcription and Cell Survival.

Molecular and cellular biology·2025

Same journal

Probabilistic RNA designability via interpretable ensemble approximation and dynamic decomposition.

Bioinformatics (Oxford, England)·2026

Same journal

Quantifying domain-specific relevance of computational biology Wikipedia articles using TF-IDF and cosine similarity.

Bioinformatics (Oxford, England)·2026

Same journal

GATSBI: improving context-aware protein embeddings through biologically motivated data splits.

Bioinformatics (Oxford, England)·2026

Same journal

BiMba: using Vision Mamba to predict protein sites that bind other proteins.

Bioinformatics (Oxford, England)·2026

Same journal

ProMeta: a meta-learning framework for robust disease diagnosis and prediction from plasma proteomics.

Bioinformatics (Oxford, England)·2026

Same journal

Is a Win-Win possible? Achieving pareto-optimal privacy-utility balance in fine-tuned genome language model embeddings against embedding reconstruction attacks.

Bioinformatics (Oxford, England)·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Aug 9, 2025

Metagenomic Analysis of Silage

Metagenomic Analysis of Silage

Published on: January 13, 2017

MeganServer: facilitating interactive access to metagenomic data on a server.

Anupam Gautam^1,2,3, Wenhuan Zeng¹, Daniel H Huson^1,2,3

¹Algorithms in Bioinformatics, Institute for Bioinformatics and Medical Informatics, University of Tübingen, Tübingen 72076, Germany.

Bioinformatics (Oxford, England)

|February 24, 2023

Summary

This summary is machine-generated.

MeganServer streamlines metagenomic data analysis by serving large datasets directly to the MEGAN (MEtaGenome ANalyzer) program via a RESTful API. This eliminates the need for time-consuming data downloads, enabling faster interactive exploration of microbial community structures.

More Related Videos

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

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

Published on: December 7, 2021

A Clinical Metaproteomics Workflow Implemented within Galaxy Bioinformatics Platform to Analyze Host-Microbiome Interactions Underlying Human Disease

A Clinical Metaproteomics Workflow Implemented within Galaxy Bioinformatics Platform to Analyze Host-Microbiome Interactions Underlying Human Disease

Published on: January 10, 2025

Related Experiment Videos

Last Updated: Aug 9, 2025

Metagenomic Analysis of Silage

Metagenomic Analysis of Silage

Published on: January 13, 2017

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

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

Published on: December 7, 2021

A Clinical Metaproteomics Workflow Implemented within Galaxy Bioinformatics Platform to Analyze Host-Microbiome Interactions Underlying Human Disease

A Clinical Metaproteomics Workflow Implemented within Galaxy Bioinformatics Platform to Analyze Host-Microbiome Interactions Underlying Human Disease

Published on: January 10, 2025

Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

Metagenomic projects generate massive datasets (hundreds of gigabytes).
Computational preprocessing and analysis are typically server-based.
Interactive exploration of results often requires downloading large data files, which is time-consuming.

Purpose of the Study:

To present MeganServer, a novel program for serving MEGAN files over the web.
To enable interactive analysis of metagenomic data in MEGAN without prior data download.
To describe various application scenarios for MeganServer.

Main Methods:

Developed MeganServer as a stand-alone program.
Implemented a RESTful API for serving MEGAN files.
Integrated MeganServer with the MEGAN software suite.

Main Results:

MeganServer facilitates direct, interactive analysis of large metagenomic datasets within MEGAN.
Eliminates the bottleneck of downloading large computed data files from servers.
Demonstrated utility across different metagenomic analysis scenarios.

Conclusions:

MeganServer significantly improves the efficiency of interactive metagenomic data exploration.
Enables seamless integration of server-based computations with desktop analysis tools.
Offers a practical solution for handling large-scale metagenomic data analysis workflows.