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Iron Hack - A symposium/hackathon focused on porphyrias, Friedreich's ataxia, and other rare iron-related diseases.

Gloria C FerreiraJenna OberstallerRenée FonsecaThomas E KellerSwamy Rakesh AdapaJustin GibbonsChengqi WangXiaoming LiuChang LiMinh PhamGuy W Dayhoff IiLinh M DuongLuis Tañón ReyesLuciano Enrique LaratelliDouglas FranzSegun FatumoAtm Golam BariAudrey FreischelLindsey FiedlerOmkar DokurKrishna SharmaDeborah CragunBen BusbyRays H Y Jiang
Published in: F1000Research (2019)
Background: Basic and clinical scientific research at the University of South Florida (USF) have intersected to support a multi-faceted approach around a common focus on rare iron-related diseases. We proposed a modified version of the National Center for Biotechnology Information's (NCBI) Hackathon-model to take full advantage of local expertise in building "Iron Hack", a rare disease-focused hackathon. As the collaborative, problem-solving nature of hackathons tends to attract participants of highly-diverse backgrounds, organizers facilitated a symposium on rare iron-related diseases, specifically porphyrias and Friedreich's ataxia, pitched at general audiences. Methods: The hackathon was structured to begin each day with presentations by expert clinicians, genetic counselors, researchers focused on molecular and cellular biology, public health/global health, genetics/genomics, computational biology, bioinformatics, biomolecular science, bioengineering, and computer science, as well as guest speakers from the American Porphyria Foundation (APF) and Friedreich's Ataxia Research Alliance (FARA) to inform participants as to the human impact of these diseases. Results: As a result of this hackathon, we developed resources that are relevant not only to these specific disease-models, but also to other rare diseases and general bioinformatics problems. Within two and a half days, "Iron Hack" participants successfully built collaborative projects to visualize data, build databases, improve rare disease diagnosis, and study rare-disease inheritance. Conclusions: The purpose of this manuscript is to demonstrate the utility of a hackathon model to generate prototypes of generalizable tools for a given disease and train clinicians and data scientists to interact more effectively.
Keyphrases
  • public health
  • global health
  • quality improvement
  • mental health
  • big data
  • healthcare
  • early onset
  • machine learning
  • genome wide
  • dna methylation
  • social media