ArticleFrontiers in genetics2020
Investigation of the Genome-Wide Genetic and Epigenetic Networks for Drug Discovery Based on Systems Biology Approaches in Colorectal Cancer.
Article in Frontiers in genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed, 10 citations in OpenAlex.
- Systems Biology Methods via Genome-Wide RNA Sequences to Investigate Pathogenic Mechanisms for Identifying Biomarkers and Constructing a DNN-Based Drug-Target Interaction Model to Predict Potential Molecular Drugs for Treating Atopic Dermatitis.International journal of molecular sciences · 2024Article
- Drug Target Identification and Drug Repurposing in Psoriasis through Systems Biology Approach, DNN-Based DTI Model and Genome-Wide Microarray Data.International journal of molecular sciences · 2023Article
- Plasma Exosome Gene Signature Differentiates Colon Cancer from Healthy Controls.Annals of surgical oncology · 2023Article
- Identifying Drug Targets of Oral Squamous Cell Carcinoma through a Systems Biology Method and Genome-Wide Microarray Data for Drug Discovery by Deep Learning and Drug Design Specifications.International journal of molecular sciences · 2022Article
- Tumor-Derived Exosomes Enriched by miRNA-124 Promote Anti-tumor Immune Response in CT-26 Tumor-Bearing Mice.Frontiers in medicine · 2021Article
- Perspective of Human Condensins Involved in Colorectal Cancer.Frontiers in pharmacology · 2021Article
- A Correlation Study of Prognostic Risk Prediction for Colorectal Cancer Based on Autophagy Signature Genes.Frontiers in oncology · 2021Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Colorectal cancer (CRC) is the third most commonly diagnosed type of cancer worldwide. The mechanisms leading to the progression of CRC are involved in both genetic and epigenetic regulations. In this study, we applied systems biology methods to identify potential biomarkers and conduct drug discovery in a computational approach. Using big database mining, we constructed a candidate protein-protein interaction network and a candidate gene regulatory network, combining them into a genome-wide genetic and epigenetic network (GWGEN). With the assistance of system identification and model selection approaches, we obtain real GWGENs for early-stage, mid-stage, and late-stage CRC. Subsequently, we extracted core GWGENs for each stage of CRC from their real GWGENs through a principal network projection method, and projected them to the Kyoto Encyclopedia of Genes and Genomes pathways for further analysis. Finally, we compared these core pathways resulting in different molecular mechanisms in each stage of CRC and identified carcinogenic biomarkers for the design of multiple-molecule drugs to prevent the progression of CRC. Based on the identified gene expression signatures, we suggested potential compounds combined with known CRC drugs to prevent the progression of CRC with querying Connectivity Map (CMap).
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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 Socratic graph.