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

Search research articles

Related Experiment Videos

Multi-aspect candidates for repositioning: data fusion methods using heterogeneous information sources.

Á Arany¹, B Bolgár, B Balogh

¹Department of Organic Chemistry, University Semmelweis H-1092 Budapest, Hogyes Endre u. 7, Hungary.

Current Medicinal Chemistry

|December 6, 2012

Summary

This study introduces a novel kernel-based data fusion method to enhance drug repositioning strategies. This approach efficiently integrates diverse information sources, improving the identification of new therapeutic applications for existing drugs.

Related Concept Videos

You might also read

Related Articles

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

Sort by

Same author

Taxamat: Automated biodiversity data management tool - Implications for microbiome studies.

Physiology international·2020

Same author

Management of Tomato Bacterial Spot in the Field by Foliar Applications of Bacteriophages and SAR Inducers.

Plant disease·2019

Same author

Improved Efficacy of Newly Formulated Bacteriophages for Management of Bacterial Spot on Tomato.

Plant disease·2019

Same author

Integration of Biological Control Agents and Systemic Acquired Resistance Inducers Against Bacterial Spot on Tomato.

Plant disease·2019

Same author

Variants in the CNR1 gene predispose to headache with nausea in the presence of life stress.

Genes, brain, and behavior·2016

Same author

A novel 3-(4,5-diphenyl-1,3-oxazol-2-yl)propanal oxime compound is a potent Transient Receptor Potential Ankyrin 1 and Vanilloid 1 (TRPA1 and V1) receptor antagonist.

Neuroscience·2016

Area of Science:

Pharmacology
Computational Chemistry
Drug Discovery

Background:

Drug repositioning is a cost-effective strategy in pharmaceutical research and development.
Effectively utilizing diverse data sources like chemical, target, and bibliometric information can promote drug repositioning.
Existing methods for integrating these diverse sources have limitations.

Purpose of the Study:

To develop and evaluate a novel, efficient approach for identifying new therapeutic applications of approved drugs and drug candidates.
To adapt a kernel-based data fusion method for drug repositioning.
To demonstrate the advantages of this method over standard approaches.

Main Methods:

A kernel-based data fusion strategy was employed, featuring multiple representations of information sources.

Related Experiment Videos

Automated weighting and statistically optimal combination of various information sources were implemented.

Automated weighting of query compound components was also incorporated.

Performance was evaluated using the Anatomical Therapeutic Chemical Classification System in a cross-validation framework.

Main Results:

Kernel-based data fusion significantly outperforms standard rank-based fusion in integrating heterogeneous information sources.
The method demonstrates superior efficiency in identifying potential new therapeutic uses for drugs.
The approach is effective for both drug repositioning and de novo drug discovery.

Conclusions:

Kernel-based data fusion offers a unique and powerful solution for drug repositioning.
This method provides a robust framework for integrating diverse data in drug discovery.
The approach has significant potential for pharmaceutical applications and further research.