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

Conservation of Protein Domains Over Different Proteins02:26

Conservation of Protein Domains Over Different Proteins

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 form...
Predicting Products: Substitution vs. Elimination02:52

Predicting Products: Substitution vs. Elimination

When a nucleophile and an alkyl halide react, nucleophilic substitution and β-elimination reactions compete to generate products.
The following factors can influence the mechanisms competing against each other:
Predicting Reaction Outcomes02:24

Predicting Reaction Outcomes

Kinetics describes the rate and path by which a reaction occurs. In contrast, thermodynamics deals with state functions and describes the properties, behavior, and components of a system. It is not concerned with the path taken by the process and cannot address the rate at which a reaction occurs. Although it does provide information about what can happen during a reaction process, it does not describe the detailed steps of what appears on an atomic or a molecular level. On the other hand,...
Sensitivity, Specificity, and Predicted Value01:13

Sensitivity, Specificity, and Predicted Value

In healthcare diagnostics, laboratory tests play a crucial role in identifying and diagnosing a wide range of medical conditions. However, interpreting test results is not always straightforward. An abnormal test result does not always confirm the presence of a disease, just as a normal result does not guarantee its absence. To assess the reliability of these diagnostic tools, healthcare practitioners rely on two key statistical indicators: sensitivity and specificity.
Sensitivity is the...
Classification of Systems-I01:26

Classification of Systems-I

Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
Conservation of Protein Domains02:26

Conservation of Protein Domains

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 form...

You might also read

Related Articles

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

Sort by
Same author

Heterogeneity in symptom burden and supportive care needs among older adults with ischemic stroke: a cross-sectional study.

BMC geriatrics·2026
Same author

The modifying effect of diabetes on the association between triglyceride to high-density lipoprotein cholesterol ratio and cardiovascular risk: a systematic review and meta-analysis.

Frontiers in cardiovascular medicine·2026
Same author

Fermentative iron reduction by a psychrotolerant Clostridium-dominant consortium enriched from Antarctic penguin-impacted soils.

Communications biology·2026
Same author

Oliceridine versus sufentanil: a systematic review and meta-analysis of postoperative nausea and vomiting.

BMC anesthesiology·2026
Same author

Breaking the barrier: from biosynthetic inhibition to multidimensional modulation of the mycobacterial cell wall in tuberculosis therapy.

Frontiers in pharmacology·2026
Same author

ChSCL9 negatively regulates citric acid accumulation via repressing PH4-PH5 module in kumquat.

Plant physiology·2026

Related Experiment Video

Updated: Jun 7, 2026

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions
06:50

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions

Published on: January 26, 2024

Predicting domain-domain interaction based on domain profiles with feature selection and support vector machines.

Alvaro J González1, Li Liao

  • 1Department of Computer and Information Sciences, University of Delaware 421 Smith Hall, Newark, DE 19716, USA.

BMC Bioinformatics
|November 2, 2010
PubMed
Summary

This study introduces a computational method for predicting domain-domain interactions (DDIs) using support vector machines and interaction profile hidden Markov models. The approach significantly improves prediction accuracy compared to existing methods.

Related Experiment Videos

Last Updated: Jun 7, 2026

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions
06:50

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions

Published on: January 26, 2024

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Structural Biology

Background:

  • Protein-protein interactions (PPIs) are crucial for cellular functions.
  • Experimental PPI prediction is costly and time-consuming.
  • Predicting domain-domain interactions (DDIs) is a key step towards accurate PPI prediction.

Purpose of the Study:

  • To develop a novel computational method for predicting DDIs.
  • To improve the accuracy of DDI prediction by leveraging domain profile information.

Main Methods:

  • Utilized support vector machines (SVMs) for classification.
  • Represented protein domains using interaction profile hidden Markov models (ipHMMs).
  • Extracted domain features using Fisher scores and selected them via singular value decomposition (SVD).

Main Results:

  • Achieved significant improvement in DDI prediction accuracy.
  • Demonstrated superior performance compared to the existing InterPreTS method.
  • Validated the method using leave-one-out cross-validation on the 3DID database.

Conclusions:

  • Domain-domain interaction prediction accuracy is enhanced by using domain profiles, feature selection (Fisher scores, SVD), and SVMs.
  • The developed method offers a more accurate computational approach to DDI prediction.
  • Datasets and source code are publicly available for further research.