ReviewInternational journal of molecular sciences2016
Neuroblastoma, a Paradigm for Big Data Science in Pediatric Oncology.
Review in International journal of molecular sciences, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
26 citing papers in PubMed, 47 citations in OpenAlex.
- Crocetin suppresses colorectal cancer progression by targeting TGM2 and inhibiting the JAK2/STAT3 pathway.Investigational new drugs · 2026Article
- Prediction of Composite Clinical Outcomes for Childhood Neuroblastoma Using Multi-Omics Data and Machine Learning.International journal of molecular sciences · 2024Article
- The Ying and Yang of Ganglioside Function in Cancer.Cancers · 2023Review
- Identification of a novel eighteen-gene signature of recurrent metastasis neuroblastoma.Journal of molecular medicine (Berlin, Germany) · 2023Article
- Clinical value and molecular mechanism of AQGPs in different tumors.Medical oncology (Northwood, London, England) · 2022Review
- Serine-Threonine Kinase Receptor Associate Protein (STRAP) confers an aggressive phenotype in neuroblastoma via regulation of Focal Adhesion Kinase (FAK).Journal of pediatric surgery · 2022Article
- Construction of a Prognostic Nomogram Based on Autophagy-Related Genes for Children With Neuroblastoma.Evolutionary bioinformatics online · 2022Article
- Article
- Multicenter study of risk factors of unplanned 30-day readmissions in pediatric oncology.Cancer reports (Hoboken, N.J.) · 2021Article
- Prognostic Value of c-MYC Expression in Patients with Peripheral Neuroblastic Tumors.International journal of general medicine · 2021Article
- Prognostic Signature of Immune Genes and Immune-Related LncRNAs in Neuroblastoma: A Study Based on GEO and TARGET Datasets.Frontiers in oncology · 2021Article
- Role of Artificial Intelligence in Fighting Antimicrobial Resistance in Pediatrics.Antibiotics (Basel, Switzerland) · 2020Review
- Treatment and revaccination of children with paraneoplastic opsoclonus-myoclonus-ataxia syndrome and neuroblastoma: The Memorial Sloan Kettering experience.Pediatric blood & cancer · 2020Article
- Emerging Role of the Macrophage Migration Inhibitory Factor Family of Cytokines in Neuroblastoma. Pathogenic Effectors and Novel Therapeutic Targets?Molecules (Basel, Switzerland) · 2020Review
- Nuclear Factor-κB Activating Protein Plays an Oncogenic Role in Neuroblastoma Tumorigenesis and Recurrence Through the Phosphatidylinositol 3-Kinase/Protein Kinase B Signaling Pathway.Frontiers in cell and developmental biology · 2020Article
- Overexpression of Macrophage Migration Inhibitory Factor and Its Homologue D-Dopachrome Tautomerase as Negative Prognostic Factor in Neuroblastoma.Brain sciences · 2019Article
- Artificial intelligence applications for pediatric oncology imaging.Pediatric radiology · 2019Review
- Deep learning for stage prediction in neuroblastoma using gene expression data.Genomics & informatics · 2019Article
- Prediction of PD-L1 Expression in Neuroblastoma via Computational Modeling.Brain sciences · 2019Article
- lncRNA SNHG16 is associated with proliferation and poor prognosis of pediatric neuroblastoma.International journal of oncology · 2019Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Pediatric cancers rarely exhibit recurrent mutational events when compared to most adult cancers. This poses a challenge in understanding how cancers initiate, progress, and metastasize in early childhood. Also, due to limited detected driver mutations, it is difficult to benchmark key genes for drug development. In this review, we use neuroblastoma, a pediatric solid tumor of neural crest origin, as a paradigm for exploring "big data" applications in pediatric oncology. Computational strategies derived from big data science-network- and machine learning-based modeling and drug repositioning-hold the promise of shedding new light on the molecular mechanisms driving neuroblastoma pathogenesis and identifying potential therapeutics to combat this devastating disease. These strategies integrate robust data input, from genomic and transcriptomic studies, clinical data, and in vivo and in vitro experimental models specific to neuroblastoma and other types of cancers that closely mimic its biological characteristics. We discuss contexts in which "big data" and computational approaches, especially network-based modeling, may advance neuroblastoma research, describe currently available data and resources, and propose future models of strategic data collection and analyses for neuroblastoma and other related diseases.
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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.