Data Analysis Tools


The initiative will support the development and enhancement of tools and methods to extract knowledge on childhood cancers from data. We must identify existing tools or develop new tools that will allow us to analyze the data to help children, adolescents, and young adults.


Answer one or more of the following questions in your response:

  • What existing tools can be adapted to make it easier to develop, maintain, and/or use childhood cancer data in a common data infrastructure?
  • What new tools need to be developed?
(@farahank)

Data Analysis Tools

Data science and imaging AI approaches to enhance performance in medical imaging in childhood cancers

The objective of this idea is to support the development and implementation of imaging informatics tools in AI applications that help the pediatric radiologists provide improved medical care for children with cancer. Problems encountered and implications may be different than in the case of adult cancers. Therefore, the research supported through this initiative must maintain a sharp focus on specific medical and radiological... more »

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(@farahank)

Data Analysis Tools

Develop quantitative imaging analytic tools to support prediction or meauserment of response to therapy of children's cancers

Promote and support the development of quantitative imaging acquisition, analysis and interpretation tools that can be used in human or machine assessment of the data to help predict or measure response to children's cancer therapy in quality of life, or survivorship studies.

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(@renci.deloitte)

Data Analysis Tools

Data Translator

Disparate data sources often hold the data in forms that are not compatible with one another and limit a researcher's ability to draw research conclusions on that data. To resolve this problem, the National Center for Advancing Translational Sciences (NCATS) launched the Biomedical Data Translator Program. UNC RENCI has been deeply involved in the development of Data Translator, which seeks to integrate multiple existing... more »

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(@agaochen)

Data Analysis Tools

Gathering childhood cancer cohorts into a single database and analysis environment with user-friendly tools

Childhood Cancer Data Initiative Ideas To accelerate childhood cancer research, scientists need tools to access and analyze genomic data that are easy for bench scientists to use and powerful enough to allow bioinformaticians to test ideas. Gathering childhood cancer cohorts into a single database and analysis environment with user-friendly tools will facilitate this. This system needs to have secure access controls... more »

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Data Analysis Tools

Commitment to democratizing access to visualization and analytical tools

The National Cancer Institute (NCI) has made a significant investment in the Genomic Data Commons (GDC) which already possesses robust analytical and visualization tools. There is a sizeable amount of genomic and phenotypic information relevant to pediatric malignancies currently residing in the database of Genotypes and Phenotypes (dbGaP). The NCI could play a role in ensuring that data in dbGaP is made available through... more »

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Data Analysis Tools

Current pediatric immune-oncology data analysis tools that can be leveraged

Through the Childhood Cancer Data initiative, the National Cancer Institute could leverage existing national infrastructure such as the Center for International Blood and Marrow Transplant Research (CIBMTR), Pediatric Health Information System, and electronic health records to define optimal therapeutic strategies for pediatric patients with hematologic cancers. Such platforms could be useful because they contain comprehensive... more »

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(@nicolevasilevsky)

Data Analysis Tools

Mondo Disease Ontology: harmonizing disease concepts around the world

We will present our work on the Mondo Disease Ontology during the poster session at the Childhood Cancer Data Initiative Symposium. The Mondo ontology is a structured representation of cross-species diseases, and provides a logic-based structure for unifying multiple disease resources, which can be used for annotation and computational integration of disease data. The poster and abstract are shared at the link below.... more »

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