ArticleDatabase : the journal of biological databases and curation2015
Colorectal cancer drug target prediction using ontology-based inference and network analysis.
Article in Database : the journal of biological databases and curation, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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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
18 citing papers in PubMed, 1 synthesis or guideline pooled it, 35 citations in OpenAlex.
- The landscape of the methodology in drug repurposing using human genomic data: a systematic review.Briefings in bioinformatics · 2024Pooled it
- Investigating combined hypoxia and stemness indices for prognostic transcripts in gastric cancer: Machine learning and network analysis approaches.Biochemistry and biophysics reports · 2025Article
- The OREGANO knowledge graph for computational drug repurposing.Scientific data · 2023Article
- Using Advanced Bioinformatics Tools to Identify Novel Therapeutic Candidates for Proliferative Vitreoretinopathy.Translational vision science & technology · 2023Article
- Identifying novel candidate compounds for therapeutic strategies in retinopathy of prematurity via computational drug-gene association analysis.Frontiers in pediatrics · 2023Article
- Using Computational Drug-Gene Analysis to Identify Novel Therapeutic Candidates for Retinal Neuroprotection.International journal of molecular sciences · 2022Article
- Using Advanced Bioinformatics Tools to Identify Novel Therapeutic Candidates for Age-Related Macular Degeneration.Translational vision science & technology · 2022Article
- Ontologies and Knowledge Graphs in Oncology Research.Cancers · 2022Review
- Cell death mechanisms induced by synergistic effects of halofuginone and artemisinin in colorectal cancer cells.International journal of medical sciences · 2022Article
- Smell Detection Agent Optimisation Framework and Systems Biology Approach to Detect Dys-Regulated Subnetwork in Cancer Data.Biomolecules · 2021Article
- Comparison Study of Computational Prediction Tools for Drug-Target Binding Affinities.Frontiers in chemistry · 2019Review
- Herb Target Prediction Based on Representation Learning of Symptom related Heterogeneous Network.Computational and structural biotechnology journal · 2019Article
- Identification of novel immune-relevant drug target genes for Alzheimer's Disease by combining ontology inference with network analysis.CNS neuroscience & therapeutics · 2018Article
- Article
- Current Strategies and Applications for Precision Drug Design.Frontiers in pharmacology · 2018Review
- Large-Scale Prediction of Drug-Target Interaction: a Data-Centric Review.The AAPS journal · 2017Review
- Predicting cancer-relevant proteins using an improved molecular similarity ensemble approach.Oncotarget · 2016Article
- Semantic Web Ontology and Data Integration: a Case Study in Aiding Psychiatric Drug Repurposing.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2016Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
Identification of novel drug targets is a critical step in drug development. Many recent studies have produced multiple types of data, which provides an opportunity to mine the relationships among them to predict drug targets. In this study, we present a novel integrative approach that combines ontology reasoning with network-assisted gene ranking to predict new drug targets. We utilized colorectal cancer (CRC) as a proof-of-concept use case to illustrate the approach. Starting from FDA-approved CRC drugs and the relationships among disease, drug, gene, pathway, and SNP in an ontology representing PharmGKB data, we inferred 113 potential CRC drug targets. We further prioritized these genes based on their relationships with CRC disease genes in the context of human protein-protein interaction networks. Thus, among the 113 potential drug targets, 15 were selected as the promising drug targets, including some genes that are supported by previous studies. Among them, EGFR, TOP1 and VEGFA are known targets of FDA-approved drugs. Additionally, CCND1 (cyclin D1), and PTGS2 (prostaglandin-endoperoxide synthase 2) have reported to be relevant to CRC or as potential drug targets based on the literature search. These results indicate that our approach is promising for drug target prediction for CRC treatment, which might be useful for other cancer therapeutics.
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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.