Neuroblastoma, a Paradigm for Big Data Science in Pediatric Oncology
AbstractPediatric 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. View Full-Text
Scifeed alert for new publicationsNever miss any articles matching your research from any publisher
- Get alerts for new papers matching your research
- Find out the new papers from selected authors
- Updated daily for 49'000+ journals and 6000+ publishers
- Define your Scifeed now
Salazar, B.M.; Balczewski, E.A.; Ung, C.Y.; Zhu, S. Neuroblastoma, a Paradigm for Big Data Science in Pediatric Oncology. Int. J. Mol. Sci. 2017, 18, 37.
Salazar BM, Balczewski EA, Ung CY, Zhu S. Neuroblastoma, a Paradigm for Big Data Science in Pediatric Oncology. International Journal of Molecular Sciences. 2017; 18(1):37.Chicago/Turabian Style
Salazar, Brittany M.; Balczewski, Emily A.; Ung, Choong Y.; Zhu, Shizhen. 2017. "Neuroblastoma, a Paradigm for Big Data Science in Pediatric Oncology." Int. J. Mol. Sci. 18, no. 1: 37.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.