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

18.7K
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.
18.7K
Conserved Binding Sites01:49

Conserved Binding Sites

4.1K
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...
4.1K
Protein Networks02:26

Protein Networks

3.9K
An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
3.9K
Globular and Fibrous Proteins02:21

Globular and Fibrous Proteins

42.9K
Many proteins can be classified into two distinct subtypes - globular or fibrous. These two types differ in their shapes and solubilities.
Globular proteins are also known as spheroproteins and typically are approximately round in shape. They contain a mix of amino acid types and contain differing sequences in their primary structures. Globular proteins have many different functions, such as enzymes, cellular messengers, and molecular transporters. These roles often require the proteins to be...
42.9K
Nucleic Acid Structure01:25

Nucleic Acid Structure

5.8K
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...
5.8K
Protein Complexes with Interchangeable Parts01:57

Protein Complexes with Interchangeable Parts

2.5K
Groups of proteins may form a complex where each protein in this complex has a different role in the overall execution of the complex’s function. Often some of the proteins in the complex can be replaced by a closely related variant to give a complex that contains many of the same components yet is functionally distinct.
The SCF ubiquitin ligase is a protein complex of five individual proteins. This complex attaches ubiquitin to other target proteins to mark them for degradation. In order...
2.5K

You might also read

Related Articles

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

Sort by
Same author

GBSC: graph-based sequence clustering method for similar short tandem repeats in protein sequences.

Bioinformatics (Oxford, England)·2026
Same author

CB-Search: a method for searching for similar protein motifs with biased compositions.

BMC bioinformatics·2026
Same author

Clinicopathological Characteristics of Acute Antibody-Mediated Rejection in Pediatric Liver Transplantation-A Single-Center Study.

Journal of clinical medicine·2026
Same author

Pathogenic mobile element insertion in the <i>MEN1</i> gene mimicking a deletion in MLPA: characterisation by long-read sequencing.

Journal of medical genetics·2026
Same author

Sex-related differences in gene expression in early-stage bladder cancer revealed by whole-transcriptome sequencing.

BMC cancer·2026
Same author

Sex- and mouse strain-related differences in body weight gain, composition of the gut microbiota, and levels of selected metabolites in response to a Western-style diet.

BMC gastroenterology·2026

Related Experiment Video

Updated: May 8, 2025

RNA Next-Generation Sequencing and a Bioinformatics Pipeline to Identify Expressed LINE-1s at the Locus-Specific Level
11:04

RNA Next-Generation Sequencing and a Bioinformatics Pipeline to Identify Expressed LINE-1s at the Locus-Specific Level

Published on: May 19, 2019

9.8K

LCRAnnotationsDB: a database of low complexity regions functional and structural annotations.

Joanna Ziemska-Legiecka1, Patryk Jarnot2, Sylwia Szymańska2

  • 1Institute of Biochemistry and Biophysics, Polish Academy of Sciences, Warsaw, 02-106, Poland. joannazl@ibb.waw.pl.

BMC Genomics
|December 28, 2024
PubMed
Summary

Low Complexity Regions (LCRs) are crucial protein segments. LCRAnnotationsDB unifies scattered functional data on these regions, organizing it by similarity and linking to Gene Ontology terms for better accessibility.

Keywords:
AnnotationDatabaseFunctionIntegrationLCDLCRLow complexity regionsProteinStructure

More Related Videos

Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration
04:41

Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration

Published on: January 9, 2020

18.9K
Comprehensive DNA Methylation Analysis Using a Methyl-CpG-binding Domain Capture-based Method in Chronic Lymphocytic Leukemia Patients
13:21

Comprehensive DNA Methylation Analysis Using a Methyl-CpG-binding Domain Capture-based Method in Chronic Lymphocytic Leukemia Patients

Published on: June 16, 2017

9.8K

Related Experiment Videos

Last Updated: May 8, 2025

RNA Next-Generation Sequencing and a Bioinformatics Pipeline to Identify Expressed LINE-1s at the Locus-Specific Level
11:04

RNA Next-Generation Sequencing and a Bioinformatics Pipeline to Identify Expressed LINE-1s at the Locus-Specific Level

Published on: May 19, 2019

9.8K
Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration
04:41

Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration

Published on: January 9, 2020

18.9K
Comprehensive DNA Methylation Analysis Using a Methyl-CpG-binding Domain Capture-based Method in Chronic Lymphocytic Leukemia Patients
13:21

Comprehensive DNA Methylation Analysis Using a Methyl-CpG-binding Domain Capture-based Method in Chronic Lymphocytic Leukemia Patients

Published on: June 16, 2017

9.8K

Area of Science:

  • Bioinformatics
  • Structural Biology
  • Computational Biology

Background:

  • Low Complexity Regions (LCRs) are protein segments characterized by low amino acid diversity.
  • LCRs are functionally significant, but information about them is fragmented across various databases and literature.
  • A centralized resource is needed to consolidate and organize LCR-related annotations.

Purpose of the Study:

  • To develop LCRAnnotationsDB, a centralized database for LCR functional annotations.
  • To unify and categorize dispersed LCR information based on functional, structural, and biological process similarities.
  • To enhance accessibility and utility of LCR data through hierarchical organization linked to Gene Ontology terms.

Main Methods:

  • Collected and curated annotations related to Low Complexity Regions from diverse sources.
  • Developed a categorization system for annotations based on functional, structural, and biological process similarity.
  • Organized categories hierarchically, linking them to relevant Gene Ontology (GO) terms.
  • Implemented the LCRAnnotationsDB database at https://lcrannotdb.lcr-lab.org/.

Main Results:

  • Successfully consolidated dispersed LCR annotations into a single, unified database.
  • Established a hierarchical categorization system for LCR annotations, improving data organization.
  • Linked LCR categories to Gene Ontology terms, facilitating deeper biological context and integration.
  • Made the LCRAnnotationsDB publicly accessible for researchers.

Conclusions:

  • LCRAnnotationsDB provides a valuable, centralized resource for LCR research.
  • The database facilitates a more comprehensive understanding of LCR functions and roles in proteins.
  • Hierarchical organization and GO term linking enhance data integration and discovery in protein science.