Jove
Visualize
Contact Us

Related Concept Videos

Synthesis and Decomposition Reactions02:17

Synthesis and Decomposition Reactions

Synthesis and decomposition are two types of redox reactions. Synthesis means to make something, whereas decomposition means to break something. The reactions are accompanied by chemical and energy changes.
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,...
Predicting Molecular Geometry02:27

Predicting Molecular Geometry

VSEPR Theory for Determination of Electron Pair Geometries
Experimental Determination of Chemical Formula02:37

Experimental Determination of Chemical Formula

The elemental makeup of a compound defines its chemical identity, and chemical formulas are the most concise way of representing this elemental makeup. When a compound’s formula is unknown, measuring the mass of its constituent elements is often the first step in determining the formula experimentally.
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:
Phylogenetic Trees03:21

Phylogenetic Trees

Phylogenetic trees come in many forms. It matters in which sequence the organisms are arranged from the bottom to the top of the tree, but the branches can rotate at their nodes without altering the information. The lines connecting individual nodes can be straight, angled, or even curved.

You might also read

Related Articles

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

Sort by
Same author

On the Number of Control Nodes in Boolean Networks With Degree Constraints.

IEEE transactions on cybernetics·2026
Same author

DiCleavePlus: A Transformer-Based Model to Detect Human Dicer Cleavage Sites Within Cleavage Patterns.

Genes to cells : devoted to molecular & cellular mechanisms·2025
Same author

Toward Environment-Sensitive Molecular Inference via Mixed Integer Linear Programming.

ACS omega·2025
Same author

Enhancing epidemic forecasting with a physics-informed spatial identity neural network.

PloS one·2025
Same author

Cycle-configuration descriptors: a novel graph-theoretic approach to enhancing molecular inference.

Journal of cheminformatics·2025
Same author

DeepGDel: Deep Learning-Based Gene Deletion Prediction Framework for Growth-Coupled Production in Genome-Scale Metabolic Models.

IEEE transactions on computational biology and bioinformatics·2025
Same journal

Linear regression models predicting strength of transcriptional activity of promoters.

Genome informatics. International Conference on Genome Informatics·2012
Same journal

Sign: large-scale gene network estimation environment for high performance computing.

Genome informatics. International Conference on Genome Informatics·2012
Same journal

Docking-calculation-based method for predicting protein-RNA interactions.

Genome informatics. International Conference on Genome Informatics·2012
Same journal

Mechanism of cell cycle disruption by multiple p53 pulses.

Genome informatics. International Conference on Genome Informatics·2012
Same journal

Database for crude drugs and Kampo medicine.

Genome informatics. International Conference on Genome Informatics·2012
Same journal

G1 and G2 arrests in response to osmotic shock are robust properties of the budding yeast cell cycle.

Genome informatics. International Conference on Genome Informatics·2011
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: May 27, 2026

Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids
08:21

Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids

Published on: April 13, 2022

A dynamic programming algorithm to predict synthesis processes of tree-structured compounds with graph grammar.

Yang Zhao1, Takeyuki Tamura, Morihiro Hayashida

  • 1Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto, 611-0011, Japan. tyoyo@kuicr.kyoto-u.ac.jp.

Genome Informatics. International Conference on Genome Informatics
|November 15, 2011
PubMed
Summary
This summary is machine-generated.

This study introduces a novel bottom-up dynamic programming algorithm for predicting organic synthesis paths. This approach efficiently generates synthesis routes for tree-structured compounds, overcoming computational limitations of previous methods.

More Related Videos

Hierarchical and Programmable One-Pot Oligosaccharide Synthesis
09:56

Hierarchical and Programmable One-Pot Oligosaccharide Synthesis

Published on: September 6, 2019

Related Experiment Videos

Last Updated: May 27, 2026

Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids
08:21

Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids

Published on: April 13, 2022

Hierarchical and Programmable One-Pot Oligosaccharide Synthesis
09:56

Hierarchical and Programmable One-Pot Oligosaccharide Synthesis

Published on: September 6, 2019

Area of Science:

  • Computational Chemistry
  • Organic Synthesis
  • Algorithm Development

Background:

  • Predicting organic synthesis paths is crucial but computationally intensive.
  • Existing methods often suffer from non-polynomial computational time.
  • Need for efficient algorithms for complex molecule synthesis.

Purpose of the Study:

  • To develop a novel bottom-up dynamic programming algorithm for predicting synthesis paths.
  • To address the computational complexity of existing methods.
  • To enable efficient synthesis prediction for tree-structured compounds.

Main Methods:

  • Transforming synthesis prediction into an unordered tree generation problem.
  • Representing compounds and reactions as unordered trees and rules.
  • Utilizing a subclass of Node Label Controlled (NLC) grammars for rule representation.

Main Results:

  • A bottom-up dynamic programming algorithm was developed.
  • The algorithm transforms synthesis into tree generation.
  • Computational results demonstrate the algorithm's effectiveness.

Conclusions:

  • The proposed algorithm offers an efficient approach to predicting synthesis paths.
  • Dynamic programming and NLC grammars provide a robust framework.
  • This method enhances computational feasibility for organic synthesis prediction.