Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...

Drug Discovery: Overview

Drug Discovery: Overview

Drug discovery is a multifaceted process involving extensive screening, testing, and optimization of lead compounds to identify potential new drugs for therapeutic use. It combines several approaches, including screening large numbers of natural products, chemical modification of known active molecules, identification of new drug targets, and rational design based on biological mechanisms and drug-receptor structure. These approaches are carried out in both academic research laboratories and...

Molecular Models

Molecular Models

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.

You might also read

Related Articles

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

Sort by

Same author

Helios serves as a suppression marker to reduce regulatory T cell function in pancreatic cancer patients.

Immunologic research·2021

Same author

Investigation of the Association between 45 Tag SNPs and Type 2 Diabetes Mellitus in Han Chinese Adults: A Prospective Cohort Study.

Public health genomics·2021

Same author

Prevalence and associated factors of poor sleep quality among Chinese returning workers during the COVID-19 pandemic.

Sleep medicine·2020

Same author

Anticancer Drug Combinations, How Far We can Go Through?

Anti-cancer agents in medicinal chemistry·2016

Same author

In situ TEM study of stability of TaRhx diffusion barriers using a novel sample preparation method.

Micron (Oxford, England : 1993)·2013

Same author

Graphene oxide capturing surface-fluorinated TiO2 nanosheets for advanced photocatalysis and the reveal of synergism reinforce mechanism.

Dalton transactions (Cambridge, England : 2003)·2013

Same journal

Ubiquitous WiFi and Acoustic Sensing: Principles, Technologies, and Applications.

Journal of computer science and technology·2023

Same journal

HXPY: A High-Performance Data Processing Package for Financial Time-Series Data.

Journal of computer science and technology·2023

Same journal

I/O Efficient Early Bursting Cohesive Subgraph Discovery in Massive Temporal Networks.

Journal of computer science and technology·2023

Same journal

Improving Friend Recommendation for Online Learning with Fine-Grained Evolving Interest.

Journal of computer science and technology·2023

Same journal

JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY.

Journal of computer science and technology·2023

Same journal

Experiments and Analyses of Anonymization Mechanisms for Trajectory Data Publishing.

Journal of computer science and technology·2022

See all related articles

Search research articles

Related Experiment Video

Updated: Aug 15, 2025

Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids

Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids

Published on: April 13, 2022

Towards Exploring Large Molecular Space: An Efficient Chemical Genetic Algorithm.

Jian-Fu Zhu¹, Zhong-Kai Hao¹, Qi Liu¹

¹Anhui Province Key Laboratory of Big Data Analysis and Application, School of Computer Science and Technology, University of Science and Technology of China, Hefei, 230026 China.

Journal of Computer Science and Technology

|January 3, 2023

Summary

This summary is machine-generated.

We developed a novel Chemical Genetic Algorithm for Large Molecular Space (CALM) to efficiently generate molecules with desired properties. CALM significantly outperforms existing deep learning and genetic algorithm methods in molecular optimization tasks.

Keywords:

artificial intelligence data mining drug discovery genetic algorithm molecular generation

More Related Videos

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

Rapid Identification of Chemical Genetic Interactions in Saccharomyces cerevisiae

Rapid Identification of Chemical Genetic Interactions in Saccharomyces cerevisiae

Published on: April 5, 2015

Related Experiment Videos

Last Updated: Aug 15, 2025

Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids

Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids

Published on: April 13, 2022

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

Rapid Identification of Chemical Genetic Interactions in Saccharomyces cerevisiae

Rapid Identification of Chemical Genetic Interactions in Saccharomyces cerevisiae

Published on: April 5, 2015

Area of Science:

Computational Chemistry
Artificial Intelligence in Drug Discovery
Molecular Informatics

Background:

Generating molecules with specific properties is crucial for drug discovery and development.
Current deep learning and genetic algorithm methods for molecular generation and optimization have limitations in efficiency and performance.

Purpose of the Study:

To propose a novel and efficient method for generating molecules with desired properties.
To improve the performance of molecular optimization tasks compared to existing state-of-the-art approaches.

Main Methods:

Introduced the Chemical Genetic Algorithm for Large Molecular Space (CALM).
Utilized a scalable molecular matrix representation.
Designed novel crossover, mutation, and mask operators informed by domain knowledge.

Main Results:

CALM demonstrated superior performance in molecular property optimization and constraint molecular optimization tasks.
Experimental results showed CALM significantly outperforms existing deep learning and genetic algorithm methods.
Statistical analysis indicated a >99% likelihood of significance for CALM's performance.

Conclusions:

CALM offers an efficient and high-performing solution for generating molecules with desired properties.
The study highlights the need for improved experimental evaluation standards in molecular generation research.
CALM provides a promising advancement for accelerating drug discovery processes.