Abstract
Precision medicine can be empowered by a personalized approach to patient care based on the patient’s unique genomic sequence. To be used in precision medicine, genomic findings must be robust, reproducible, and experimental data capture should adhere to FAIR Data Guiding Principles. Moreover, precision medicine requires standardization that extends beyond wet lab procedures to computational methods.
Rapidly developing standardization technologies improves communication of genomic sequencing by introducing concepts such as error domain, usability domain, validation kit, and provenance information. These advancements allow data provenance to be standardized and ensure interoperability. Thus, a resulting bioinformatics computation instance that includes these advancements can be easily communicated, repeated and compared by scientists, regulators, clinicians and others, allowing a greater range of practical applications.
Rapidly developing standardization technologies improves communication of genomic sequencing by introducing concepts such as error domain, usability domain, validation kit, and provenance information. These advancements allow data provenance to be standardized and ensure interoperability. Thus, a resulting bioinformatics computation instance that includes these advancements can be easily communicated, repeated and compared by scientists, regulators, clinicians and others, allowing a greater range of practical applications.