ArticleBioMed research international2016
A Systematic Framework for Drug Repositioning from Integrated Omics and Drug Phenotype Profiles Using Pathway-Drug Network.
Article in BioMed research international, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
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Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Redefining Breast Cancer Care by Harnessing Computational Drug Repositioning.Medicina (Kaunas, Lithuania) · 2025Review
- Reconciling multiple connectivity-based systems biology methods for drug repurposing.Briefings in bioinformatics · 2025Review
- Screening and transcriptomic analysis of anti-Frontiers in microbiology · 2025Article
- Insight into Mantle Cell Lymphoma Pathobiology, Diagnosis, and Treatment Using Network-Based and Drug-Repurposing Approaches.International journal of molecular sciences · 2024Article
- Drug repositioning prediction for psoriasis using the adverse event reporting database.Frontiers in medicine · 2023Article
- Introducing Critical Genes in Response to Photodynamic Therapy: A Network Analysis.Journal of lasers in medical sciences · 2023Article
- Computational Analysis of Pathogenetic Pathways in Alzheimer's Disease and Prediction of Potential Therapeutic Drugs.Brain sciences · 2022Article
- Evaluating the performance of drug-repurposing technologies.Drug discovery today · 2022Review
- Drug Repositioning and Subgroup Discovery for Precision Medicine Implementation in Triple Negative Breast Cancer.Cancers · 2021Article
- Topological network measures for drug repositioning.Briefings in bioinformatics · 2021Article
- Therapeutic Targeting of Repurposed Anticancer Drugs in Alzheimer's Disease: Using the Multiomics Approach.ACS omega · 2021Article
- Drug repurposing for breast cancer therapy: Old weapon for new battle.Seminars in cancer biology · 2021Review
- Exploratory Analysis of iPSCS-Derived Neuronal Cells as Predictors of Diagnosis and Treatment of Alzheimer Disease.Brain sciences · 2020Article
- A Discovery of Clinically Approved Formula FBRP for Repositioning to Treat HCC by Inhibiting PI3K/AKT/NF-κB Activation.Molecular therapy. Nucleic acids · 2020Article
- Transcriptome-Guided Drug Repositioning.Pharmaceutics · 2019Article
- Integrated transcriptomics reveals master regulators of lung adenocarcinoma and novel repositioning of drug candidates.Cancer medicine · 2019Article
- A review of computational drug repurposing.Translational and clinical pharmacology · 2019Review
- Guanabenz Acetate Induces Endoplasmic Reticulum Stress-Related Cell Death in Hepatocellular Carcinoma Cells.Journal of pathology and translational medicine · 2019Article
- Changing Trends in Computational Drug Repositioning.Pharmaceuticals (Basel, Switzerland) · 2018Review
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Drug repositioning offers new clinical indications for old drugs. Recently, many computational approaches have been developed to repurpose marketed drugs in human diseases by mining various of biological data including disease expression profiles, pathways, drug phenotype expression profiles, and chemical structure data. However, despite encouraging results, a comprehensive and efficient computational drug repositioning approach is needed that includes the high-level integration of available resources. In this study, we propose a systematic framework employing experimental genomic knowledge and pharmaceutical knowledge to reposition drugs for a specific disease. Specifically, we first obtain experimental genomic knowledge from disease gene expression profiles and pharmaceutical knowledge from drug phenotype expression profiles and construct a pathway-drug network representing a priori known associations between drugs and pathways. To discover promising candidates for drug repositioning, we initialize node labels for the pathway-drug network using identified disease pathways and known drugs associated with the phenotype of interest and perform network propagation in a semisupervised manner. To evaluate our method, we conducted some experiments to reposition 1309 drugs based on four different breast cancer datasets and verified the results of promising candidate drugs for breast cancer by a two-step validation procedure. Consequently, our experimental results showed that the proposed framework is quite useful approach to discover promising candidates for breast cancer treatment.
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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.