Dept. of Medical Informatics and Outcomes Research
Oregon Health & Science University
Background: Bridging the gap between genotype and phenotype is one of the foremost goals of biomedicine, and consequently biomedical informatics. Effective networking between biologists and clinicians to augment biomedical technology with genotypic and phenotypic knowledge will accelerate the translational research process and enhance the possibility of bridging the gap toward an integrative genotype-phenotype system that could be incorporated in patients' personal medical records. Methods: The methods for this project included a systematic review of articles describing systems with an integration of phenotypic and genotypic data. A subset of these systems were scored on quality measures. The scoring method assigned points based on a scale of (0, 1-3), in accordance to a modified Matrix Criteria System for evaluation and scaling. SPSS 12.0 and Microsoft Excel were used to carry out the data analysis. Results: Based on the literature review, there are 107 different projects worldwide which are related directly or indirectly with the integration of phenotypic and genotypic data. The majority of the projects are centered in USA 37% followed by the UK 14% then by France 7%. Collaborative projects in Europe represented 10% of the worldwide projects. The international community collaborative work constituted 3% of the projects. A detailed analysis was conducted on two of the high scoring projects (PharmGKB and PhenomicDB). Database functions as a major scoring criterion was employed to critically compare these two projects. The database functions category includes user interface, database design, reporting, technology & platforms, and performance. Conclusion: Future genomic medicine clinicians will need to use advanced knowledge and well calculated diagnostic tests in order to provide targeted treatments to their patients on the road to personalized medical care.
School of Medicine
Al Sanousi, Ali A., "The integration of phenotypic and genotypic data : a systematic review and evaluation of interoperability models : capstone project" (2007). Scholar Archive. 699.