ArticleJournal of cheminformatics2014
Prediction of novel drug indications using network driven biological data prioritization and integration.
Article in Journal of cheminformatics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed, 51 citations in OpenAlex.
- Prediction of drug-disease associations based on reinforcement symmetric metric learning and graph convolution network.Frontiers in pharmacology · 2024Article
- Investigating the potential anticancer activities of antibiotics as topoisomerase II inhibitors and DNA intercalators:Journal of enzyme inhibition and medicinal chemistry · 2023Article
- Drug repositioning: A bibliometric analysis.Frontiers in pharmacology · 2022Review
- Systems Pharmacology-Based Precision Therapy and Drug Combination Discovery for Breast Cancer.Cancers · 2021Article
- A data-driven methodology towards evaluating the potential of drug repurposing hypotheses.Computational and structural biotechnology journal · 2021Article
- cando.py: Open Source Software for Predictive Bioanalytics of Large Scale Drug-Protein-Disease Data.Journal of chemical information and modeling · 2020Article
- Realizing drug repositioning by adapting a recommendation system to handle the process.BMC bioinformatics · 2018Article
- Prediction of drugs having opposite effects on disease genes in a directed network.BMC systems biology · 2016Article
- BBMRI-ERIC as a resource for pharmaceutical and life science industries: the development of biobank-based Expert Centres.European journal of human genetics : EJHG · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundWith the rapid development of high-throughput genomic technologies and the accumulation of genome-wide datasets for gene expression profiling and biological networks, the impact of diseases and drugs on gene expression can be comprehensively characterized. Drug repositioning offers the possibility of reduced risks in the drug discovery process, thus it is an essential step in drug development.
resultsComputational prediction of drug-disease interactions using gene expression profiling datasets and biological networks is a new direction in drug repositioning that has gained increasing interest. We developed a computational framework to build disease-drug networks using drug- and disease-specific subnetworks. The framework incorporates protein networks to refine drug and disease associated genes and prioritize genes in disease and drug specific networks. For each drug and disease we built multiple networks using gene expression profiling and text mining. Finally a logistic regression model was used to build functional associations between drugs and diseases.
conclusionsWe found that representing drugs and diseases by genes with high centrality degree in gene networks is the most promising representation of drug or disease subnetworks.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.