ArticleBMC bioinformatics2020
Developing the novel bioinformatics algorithms to systematically investigate the connections among survival time, key genes and proteins for Glioblastoma multiforme.
Article in BMC bioinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed, 14 citations in OpenAlex.
- Quantitative assessment of the associations between MTR and MTRR gene polymorphisms and glioma risk.Discover oncology · 2025Article
- Developing a multiomics data-based mathematical model to predict colorectal cancer recurrence and metastasis.BMC medical informatics and decision making · 2025Article
- Key genes altered in glioblastoma based on bioinformatics (Review).Oncology letters · 2025Review
- Re-examination of statistical relationships between dietary fats and other risk factors, and cardiovascular disease, based on two crucial datasets.Quantitative biology (Beijing, China) · 2024Article
- An integrated platform forFrontiers in genetics · 2022Article
- Developing an Embedding, Koopman and Autoencoder Technologies-Based Multi-Omics Time Series Predictive Model (EKATP) for Systems Biology research.Frontiers in genetics · 2021Article
Corrections and comments
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Authors and funding
8 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGlioblastoma multiforme (GBM) is one of the most common malignant brain tumors and its average survival time is less than 1 year after diagnosis.
resultsFirstly, this study aims to develop the novel survival analysis algorithms to explore the key genes and proteins related to GBM. Then, we explore the significant correlation between AEBP1 upregulation and increased EGFR expression in primary glioma, and employ a glioma cell line LN229 to identify relevant proteins and molecular pathways through protein network analysis. Finally, we identify that AEBP1 exerts its tumor-promoting effects by mainly activating mTOR pathway in Glioma.
conclusionsWe summarize the whole process of the experiment and discuss how to expand our experiment in the future.
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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.