Jove
Visualize
Contact Us

Related Concept Videos

Genome Annotation and Assembly03:36

Genome Annotation and Assembly

19.3K
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.
19.3K

You might also read

Related Articles

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

Sort by
Same author

Peer influence decay and behavioral diffusion in adolescent networks: A simulation approach.

Science (New York, N.Y.)·2026
Same author

Jasmonate signaling and prey nutrient availability trigger distinct biochemical responses in the Drosera capensis feeding cycle.

Plant physiology·2026
Same author

Design and Analysis of Untargeted Metabolomics Experiments.

Current protocols·2025
Same author

Jasmonate-induced prey response in the carnivorous plant <i>Drosera capensis</i>.

bioRxiv : the preprint server for biology·2025
Same author

Mini-αA-crystallin protects a client lens protein from catastrophic aggregation due to heat stress.

Protein science : a publication of the Protein Society·2025
Same author

Endogenous competition and the underrealized reproduction of infectious diseases.

Proceedings of the National Academy of Sciences of the United States of America·2025
Same journal

Leveraging target enrichment and genome skimming (Hyb-Seq) of herbarium collections to unlock timber DNA barcoding.

Applications in plant sciences·2026
Same journal

Detecting cryptic ghost lineage introgression in four-taxon genomic datasets.

Applications in plant sciences·2026
Same journal

HapAsmbl: A reference-aided pipeline for assembling haplotypes in Nanopore amplicon sequence data of polymorphic populations.

Applications in plant sciences·2026
Same journal

HybSuite: An integrated pipeline for hybrid capture phylogenomics from reads to trees.

Applications in plant sciences·2026
Same journal

Detecting introgression from phylogenetic invariant site patterns using machine learning.

Applications in plant sciences·2026
Same journal

tanggle: An R package for the visualization of phylogenetic networks.

Applications in plant sciences·2026
See all related articles
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 Experiment Video

Updated: Sep 12, 2025

An Integrated Approach for Microprotein Identification and Sequence Analysis
09:37

An Integrated Approach for Microprotein Identification and Sequence Analysis

Published on: July 12, 2022

3.5K

The Computer-Assisted Sequence Annotation (CASA) workflow for enzyme discovery.

Gemma R Takahashi1, Franchesca M Cumpio1, Carter T Butts2

  • 1Department of Molecular Biology and Biochemistry University of California Irvine 92697-3900 California USA.

Applications in Plant Sciences
|August 6, 2025
PubMed
Summary
This summary is machine-generated.

Identifying suitable enzyme candidates from vast sequence data is challenging. Computer-Assisted Sequence Annotation (CASA) provides detailed sequence and structural information to aid in selecting proteins for further biochemical study.

Keywords:
Drosera capensisenzyme discoverygenome annotationproteaseprotein sequence analysisprotein sequence annotation

More Related Videos

A Clinical Metaproteomics Workflow Implemented within Galaxy Bioinformatics Platform to Analyze Host-Microbiome Interactions Underlying Human Disease
09:52

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

Published on: January 10, 2025

730
Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins
05:08

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins

Published on: July 8, 2025

361

Related Experiment Videos

Last Updated: Sep 12, 2025

An Integrated Approach for Microprotein Identification and Sequence Analysis
09:37

An Integrated Approach for Microprotein Identification and Sequence Analysis

Published on: July 12, 2022

3.5K
A Clinical Metaproteomics Workflow Implemented within Galaxy Bioinformatics Platform to Analyze Host-Microbiome Interactions Underlying Human Disease
09:52

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

Published on: January 10, 2025

730
Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins
05:08

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins

Published on: July 8, 2025

361

Area of Science:

  • Biochemistry
  • Bioinformatics
  • Genomics

Background:

  • The increasing volume of nucleic acid sequencing data presents a challenge in enzyme discovery.
  • Current annotation methods often rely on sequence similarity alone, which is insufficient for selecting promising enzyme candidates.
  • Detailed sequence and structural information is crucial for effective enzyme characterization.

Purpose of the Study:

  • To introduce a novel computational workflow for enhanced protein annotation.
  • To automate key aspects of novel protein characterization for enzyme discovery.
  • To generate human-interpretable annotations that go beyond basic sequence similarity.

Main Methods:

  • Development of Computer-Assisted Sequence Annotation (CASA), a Python-based workflow.
  • Automating the generation of highly informative and richly annotated sequence alignments.
  • Demonstration using an enzyme from the *Drosera capensis* genome.

Main Results:

  • CASA produces detailed annotations comparing novel sequences to known references.
  • Annotations include predicted function, active site residues, disulfide bonds, and substrate-binding sites.
  • The workflow successfully characterized an enzyme from *Drosera capensis*.

Conclusions:

  • Detailed annotations and protein structure prediction are vital for selecting enzyme targets from sequence data.
  • CASA facilitates the identification of suitable protein targets for biochemistry and structural biology.
  • The CASA toolchain is freely available, promoting broader application in enzyme discovery.