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 Experiment Video

Updated: Oct 15, 2025

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.3K

A drug repositioning algorithm based on a deep autoencoder and adaptive fusion.

Peng Chen1, Tianjiazhi Bao1, Xiaosheng Yu1

  • 1College of Computer and Information Technology, China Three Gorges University, Hubei, China.

BMC Bioinformatics
|October 31, 2021
PubMed
Summary

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

Expression of kenaf mitochondrial chimeric genes HM184 causes male sterility in transgenic tobacco plants.

Mitochondrial DNA·2014
Same author

A general route towards defect and pore engineering in graphene.

Small (Weinheim an der Bergstrasse, Germany)·2014
Same author

Telomerase triggered drug release using a SERS traceable nanocarrier.

IEEE transactions on nanobioscience·2014
Same author

Analysis of 24-hour monitoring of intraocular pressure in 1055 eyes.

Eye science·2014
Same author

The variations in the IL1RL1 gene and susceptibility to preeclampsia.

Immunological investigations·2014
Same author

Three-dimensional graphene-carbon nanotube hybrid for high-performance enzymatic biofuel cells.

ACS applied materials & interfaces·2014

This study introduces a novel drug repositioning algorithm using deep autoencoders and adaptive fusion to improve precision and efficiency. The method effectively integrates diverse data sources for enhanced drug discovery and clinical trial support.

Area of Science:

  • Computational drug discovery
  • Pharmacology
  • Bioinformatics

Background:

  • Drug repositioning offers a cost-effective alternative to de novo drug development.
  • Existing computational methods face challenges with data sparseness and traditional data fusion techniques.

Purpose of the Study:

  • To develop an advanced drug repositioning algorithm addressing limitations of existing methods.
  • To enhance precision and efficiency in multisource data fusion for drug repositioning.

Main Methods:

  • Utilized a deep autoencoder for dimension reduction and feature representation of integrated drug data (target proteins, chemical structures).
  • Computed drug-disease associations, drug target proteins, drug chemical structures, and drug side effects.
  • Employed adaptive fusion to integrate diverse data sources for predicting drug-disease associations.
Keywords:
Adaptive fusionDeep autoencoderDrug repositioning

Related Experiment Videos

Last Updated: Oct 15, 2025

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.3K

Main Results:

  • The proposed algorithm demonstrated superior precision and recall rates compared to existing methods (DRCFFS, SLAMS, BADR).
  • Effectively handled data sparseness, improving multisource data fusion efficiency.
  • Successfully characterized dense and abstract feature representations of drugs.

Conclusions:

  • The developed algorithm aids in identifying novel therapeutic uses for existing drugs.
  • Provides valuable auxiliary support for drug repositioning clinical trials, exemplified by a case study on Alzheimer's disease.