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

Ranks01:02

Ranks

Unlike parametric methods, nonparametric statistics are ideal for nominal and ordinal data, requiring fewer assumptions about the population's nature or distribution. This makes nonparametric methods easier to apply and interpret, as they do not depend on parameters like mean or standard deviation. One common approach in nonparametric analysis is to sort data according to a specific criterion. For instance, we might arrange weather data from hottest to coldest days in a month or rank cities...
Spearman's Rank Correlation Test01:20

Spearman's Rank Correlation Test

Spearman's rank correlation test, also known as Spearman's rho, is a nonparametric method for assessing the strength and direction of association between two variables. This test is particularly valuable when the data distribution is unknown or when the assumption of normality does not hold. Named after the English psychologist and statistician Dr. Charles Edward Spearman, it serves as the nonparametric counterpart to Pearson's correlation coefficient.
Spearman's test calculates correlation by...
Nucleophiles02:30

Nucleophiles

The word “nucleophile” has a Greek root and translates to nucleus-loving. Nucleophiles are either negatively charged or neutral species with a pair of electrons in a high-energy occupied molecular orbital (HOMO). As these species tend to donate electron pairs, nucleophiles are considered Lewis bases as well. Negatively charged species, like OH−, Cl−, or HS−, with one or several pairs of electrons, are typically nucleophiles. Similarly, neutral species such as ammonia, amines, water, and alcohol...
Predicting Products: SN1 vs. SN202:27

Predicting Products: SN1 vs. SN2

Nucleophilic substitution reactions of alkyl halides can proceed via an SN1 or an SN2 mechanism. While in SN2 reactions, the nucleophile attacks the substrate simultaneously as the leaving group departs, in SN1 reactions, the substrate first dissociates to give the carbocation intermediate. Various factors such as the structure of the substrate, the strength of the nucleophile, and the nature of the solvent promote one mechanism over the other.
With increased substitution on the alkyl halide,...
Molecular Structure and Acidity02:34

Molecular Structure and Acidity

An acid can be deprotonated to form a conjugate base or an anion. If the produced anion is more stable, then the acid is stronger. On the contrary, if the anion is unstable, then the acid is weaker. Hence, to determine the acidity of the compound, the stability of its conjugate base is studied using various factors.
The size effect explains the change in atomic size on acidity. When comparing the acids formed from elements that belong to the same column in the periodic table, their atomic sizes...
Conserved Binding Sites01:49

Conserved Binding Sites

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 analyses the...

You might also read

Related Articles

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

Sort by
Same author

Total Pedicle Preservation Mastopexy: Technique, Safety, and Long-term Results.

Aesthetic surgery journal. Open forum·2026
Same author

ATR-FTIR analysis of temperature-dependent changes in extracellular vesicles and associated released components.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy·2026
Same author

Volatolomic analysis of extracellular vesicles extracted from cultured cells.

Talanta·2026
Same author

On the State of NLP Approaches to Modeling Depression in Social Media: A Post-COVID-19 Outlook.

IEEE journal of biomedical and health informatics·2025
Same author

Identification of putative volatile biomarkers of canine leishmaniasis in dog's breath and hair employing a novel algorithm for automated chromatographic peak detection and matching.

Analytical and bioanalytical chemistry·2024
Same author

Breast implant-associated anaplastic large cell lymphoma in Romania: First case series of all documented cases.

Journal of plastic, reconstructive & aesthetic surgery : JPRAS·2024
Same journal

Analysis of strength degradation of coal and rock masses and stability of mined areas under long term immersion environment.

PloS one·2026
Same journal

Biogenic Silver-Selenium nanocomposite with anticancer activity and potent efficacy against vancomycin-resistant Staphylococcus aureus.

PloS one·2026
Same journal

Preparation and physicochemical characterization of a biodegradable chitosan/carboxymethyl cellulose hydrogel synthesized in NaOH/urea medium.

PloS one·2026
Same journal

Action-guilt, survivor-guilt, and depression in combat-related PTSD.

PloS one·2026
Same journal

Explainable machine learning for predicting activities of daily living at discharge in stroke patients: A retrospective study using SHAP interpretability.

PloS one·2026
Same journal

Deep learning based two-way feature depiction model for brain tumor detection.

PloS one·2026
See all related articles

Related Experiment Video

Updated: May 21, 2026

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
07:08

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

An efficient rank based approach for closest string and closest substring.

Liviu P Dinu1, Radu Ionescu

  • 1Faculty of Mathematics and Computer Science, University of Bucharest, Bucharest, Romania. ldinu@fmi.unibuc.ro

Plos One
|June 8, 2012
PubMed
Summary
This summary is machine-generated.

This study introduces a novel genetic algorithm using rank distance to solve complex string problems like closest string and closest substring. Results show rank distance outperforms other measures for DNA sequence analysis.

More Related Videos

A Protocol for Computer-Based Protein Structure and Function Prediction
16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

Related Experiment Videos

Last Updated: May 21, 2026

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
07:08

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

A Protocol for Computer-Based Protein Structure and Function Prediction
16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

Area of Science:

  • Computational Biology
  • Bioinformatics
  • Algorithmic Science

Background:

  • NP-hard problems like closest string and substring are computationally intensive.
  • Existing distance measures (Hamming, Levenshtein) have limitations for certain sequence analyses.
  • Genetic algorithms offer a robust framework for tackling complex optimization problems.

Purpose of the Study:

  • To introduce a novel genetic algorithm approach utilizing rank distance.
  • To apply this approach to solve the NP-hard closest string and closest substring problems.
  • To compare the efficacy of rank distance against other string distance metrics.

Main Methods:

  • Development of two distinct genetic algorithms, each employing rank distance in its fitness function.
  • Implementation of specific genetic operations tailored for each problem.
  • Comparative analysis against genetic algorithms using Hamming and Levenshtein distances.

Main Results:

  • Genetic algorithms incorporating rank distance demonstrated superior performance.
  • Rank distance proved more effective than Hamming and Levenshtein distances in experiments.
  • The proposed algorithms achieved optimal results on real DNA sequences.

Conclusions:

  • Rank distance is a highly effective metric for solving NP-hard string problems within genetic algorithms.
  • This approach offers a significant improvement for analyzing DNA sequences.
  • The developed genetic algorithms provide a powerful tool for bioinformatics challenges.