ArticleComputational and structural biotechnology journal2023
A network medicine approach for identifying diagnostic and prognostic biomarkers and exploring drug repurposing in human cancer.
Article in Computational and structural biotechnology journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed, 33 citations in OpenAlex.
- MSF-HierGNN: a multi-source substructure-fusion hierarchical GNN method and web server to predict molecular property for drug design.Briefings in bioinformatics · 2026Article
- Applications of large-scale artificial intelligence models in bioinformatics.Quantitative biology (Beijing, China) · 2026Review
- Diffusion Model-Based Multi-Channel EEG Representation and Forecasting for Early Epileptic Seizure Warning.Interdisciplinary sciences, computational life sciences · 2026Article
- Network-informed deconvolution of bulk immune gene co-expression reveals single-cell programs and spatial organization.Frontiers in immunology · 2026Article
- SOX10, MITF, and microRNAs: Decoding their interplay in regulating melanoma plasticity.International journal of cancer · 2025Review
- Integrative analysis of RAS signaling effectors reveals stage-dependent oncogenic patterns in colon adenocarcinoma.Biotechnology reports (Amsterdam, Netherlands) · 2025Article
- ImmuProgML: machine learning-based dissection of cancer-immune dynamics during tumor progression to improve immunotherapy.Journal of translational medicine · 2025Article
- DGHNN: a deep graph and hypergraph neural network for pan-cancer related gene prediction.Bioinformatics (Oxford, England) · 2025Article
- Developing a multiomics data-based mathematical model to predict colorectal cancer recurrence and metastasis.BMC medical informatics and decision making · 2025Article
- Article
- CpG Island Definition and Methylation Mapping of the T2T-YAO Genome.Genomics, proteomics & bioinformatics · 2024Article
- A comprehensive review of artificial intelligence for pharmacology research.Frontiers in genetics · 2024Review
- Artificial Intelligence and Complex Network Approaches Reveal Potential Gene Biomarkers for Hepatocellular Carcinoma.International journal of molecular sciences · 2023Article
- Mathematical modeling of regulatory networks of intracellular processes - Aims and selected methods.Computational and structural biotechnology journal · 2023Review
- Network-based drug repurposing for HPV-associated cervical cancer.Computational and structural biotechnology journal · 2023Article
- Unlocking therapeutic potential: integration of drug repurposing and immunotherapy for various disease targeting.American journal of translational research · 2023Review
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 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cancer is a heterogeneous disease mainly driven by abnormal gene perturbations in regulatory networks. Therefore, it is appealing to identify the common and specific perturbed genes from multiple cancer networks. We developed an integrative network medicine approach to identify novel biomarkers and investigate drug repurposing across cancer types. We used a network-based method to prioritize genes in cancer-specific networks reconstructed using human transcriptome and interactome data. The prioritized genes show extensive perturbation and strong regulatory interaction with other highly perturbed genes, suggesting their vital contribution to tumorigenesis and tumor progression, and are therefore regarded as cancer genes. The cancer genes detected show remarkable performances in discriminating tumors from normal tissues and predicting survival times of cancer patients. Finally, we developed a network proximity approach to systematically screen drugs and identified dozens of candidates with repurposable potential in several cancer types. Taken together, we demonstrated the power of the network medicine approach to identify novel biomarkers and repurposable drugs in multiple cancer types. We have also made the data and code freely accessible to ensure reproducibility and reusability of the developed computational workflow.
Indexed as
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.