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

Nucleic Acid Structure01:25

Nucleic Acid Structure

10.5K
The pentose sugar in DNA is deoxyribose, while in RNA the pentose sugar is ribose. The difference between the sugars is the presence of the hydroxyl group on the ribose's second carbon and a hydrogen on the deoxyribose's second carbon. The phosphate residue attaches to the hydroxyl group of the 5′ carbon of one sugar and the hydroxyl group of the 3′ carbon of the sugar of the next nucleotide, which forms  a 5′ to 3′ phosphodiester linkage.
DNA Structure
DNA...
10.5K
Conserved Binding Sites01:49

Conserved Binding Sites

5.3K
Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally...
5.3K
Molecular Models02:00

Molecular Models

45.8K
Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.
45.8K
Conservation of Protein Domains Over Different Proteins02:26

Conservation of Protein Domains Over Different Proteins

15.2K
Protein domains are small structurally independent units that are part of a single amino acid chain.  Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
A limited set of protein domains often duplicate and recombine during evolution. These domains can be organized in different combinations to...
15.2K
Modern Molecular Taxonomy01:29

Modern Molecular Taxonomy

873
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...
873
Nucleic Acids and Nucleotides01:20

Nucleic Acids and Nucleotides

16.7K
Nucleic acids are the most important macromolecules for the continuity of life. They carry the cell's genetic blueprint and have instructions for its functioning. The two main types of nucleic acids are deoxyribonucleic acid (DNA) and ribonucleic acid (RNA).
Deoxyribonucleic Acid (DNA)
DNA is the genetic material in all living organisms, ranging from single-celled bacteria to multicellular mammals. It is in the nucleus of eukaryotes and the organelles such as chloroplasts and mitochondria....
16.7K

You might also read

Related Articles

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

Sort by
Same author

Comparison of oral fluids and pooled pen fecal samples for detection of Lawsonia intracellularis by qPCR using Bayesian latent class analysis.

Preventive veterinary medicine·2026
Same author

SQUIRREL: Balancing design automation and user interaction in a computational tool for designing segmented concrete shells.

International journal of architectural computing : IJAC·2026
Same author

A Wireless Photoplethysmography Chest Patch for Continuous Vital Sign Monitoring: A Clinical Validation Study in Intensive Care Patients.

Acta anaesthesiologica Scandinavica·2026
Same author

Wearable and wireless continuous monitoring for early detection of clinical deterioration in high-risk inpatients: a scoping review.

Intensive & critical care nursing·2026
Same author

Feline leukocyte immunophenotyping: an optimised whole-blood flow cytometry protocol.

MethodsX·2026
Same author

Strengthening medical education through health policy and management training: a cross-sectional study among Portuguese medical students.

Frontiers in public health·2026

Related Experiment Video

Updated: Apr 18, 2026

A Practical Guide to Phylogenetics for Nonexperts
12:00

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

36.3K

Learning HMMs for nucleotide sequences from amino acid alignments.

Carlos N Fischer1, Claudia M A Carareto1, Renato A C dos Santos1

  • 1Department of Statistics, Applied Maths, and Computer Science, UNESP - São Paulo State University, Rio Claro, SP, Brazil, Department of Biology, UNESP-São Paulo State University, São José do Rio Preto, SP, Brazil, Institute of Biosciences, UNESP-São Paulo State University, Rio Claro, SP, Brazil, Department of Computer Science, UFSCar-Federal University of São Carlos, São Carlos, SP, Brazil, Department of Computer Science, USP-University of São Paulo, São Carlos, SP, Brazil, Department of Computer Science, KU Leuven, Leuven, Belgium and Department of Public Health and Primary Care, KU Leuven Kulak, Kortrijk, Belgium.

Bioinformatics (Oxford, England)
|February 2, 2015
PubMed
Summary

This study introduces a streamlined method for identifying protein domains using nucleotide-based profile hidden Markov models (profile HMMs). The new approach directly searches genomes, simplifying the process compared to traditional amino acid-based methods.

More Related Videos

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
08:57

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

16.7K
Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information
09:37

Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information

Published on: August 15, 2019

10.6K

Related Experiment Videos

Last Updated: Apr 18, 2026

A Practical Guide to Phylogenetics for Nonexperts
12:00

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

36.3K
Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
08:57

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

16.7K
Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information
09:37

Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information

Published on: August 15, 2019

10.6K

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Profile hidden Markov models (profile HMMs) are effective for protein family classification and domain searching.
  • Current methods often involve searching amino acid (AA) profiles against nucleotide (NT) sequences, requiring extensive data processing.

Purpose of the Study:

  • To develop a more direct and efficient method for protein domain searching in genomic sequences.
  • To enable the direct application of profile HMMs on genomic data without intermediate AA sequence conversion.

Main Methods:

  • Conversion of amino acid (AA) alignments into nucleotide (NT) alignments.
  • Training of nucleotide-based profile HMMs using the converted NT alignments.
  • Direct application of NT-based profile HMMs on genome sequences.

Main Results:

  • A novel workflow for generating NT-based profile HMMs from AA data.
  • Elimination of the need for six-frame translation of genomic NT sequences.
  • Reduced data processing and improved efficiency in domain searching.

Conclusions:

  • The proposed method offers a more direct and computationally efficient approach to protein domain identification.
  • This strategy simplifies the bioinformatics pipeline for searching protein domains within large-scale genomic datasets.