@article {363,
	title = {International Cooperation to Enable the Diagnosis of All Rare Genetic Diseases.},
	journal = {Am J Hum Genet},
	volume = {100},
	year = {2017},
	month = {2017 May 04},
	pages = {695-705},
	abstract = {<p>Provision of a molecularly confirmed diagnosis in a timely manner for children and adults with rare genetic diseases shortens their "diagnostic odyssey," improves disease management, and fosters genetic counseling with respect to recurrence risks while assuring reproductive choices. In a general clinical genetics setting, the current diagnostic rate is approximately 50\%, but for those who do not receive a molecular diagnosis after the initial genetics evaluation, that rate is much lower. Diagnostic success for these more challenging affected individuals depends to a large extent on progress in the discovery of genes associated with, and mechanisms underlying, rare diseases. Thus, continued research is required for moving toward a more complete catalog of disease-related genes and variants. The International Rare Diseases Research Consortium (IRDiRC) was established in 2011 to bring together researchers and organizations invested in rare disease research to develop a means of achieving molecular diagnosis for all rare diseases. Here, we review the current and future bottlenecks to gene discovery and suggest strategies for enabling progress in this regard. Each successful discovery will define potential diagnostic, preventive, and therapeutic opportunities for the corresponding rare disease, enabling precision medicine for this patient population.</p>},
	keywords = {Databases, Factual, Exome, Genome, Human, Humans, International Cooperation, Rare Diseases},
	issn = {1537-6605},
	doi = {10.1016/j.ajhg.2017.04.003},
	author = {Boycott, Kym M and Rath, Ana and Chong, Jessica X and Hartley, Taila and Alkuraya, Fowzan S and Baynam, Gareth and Brookes, Anthony J and Brudno, Michael and Carracedo, Angel and den Dunnen, Johan T and Dyke, Stephanie O M and Estivill, Xavier and Goldblatt, Jack and Gonthier, Catherine and Groft, Stephen C and Gut, Ivo and Hamosh, Ada and Hieter, Philip and H{\"o}hn, Sophie and Hurles, Matthew E and Kaufmann, Petra and Knoppers, Bartha M and Krischer, Jeffrey P and Macek, Milan and Matthijs, Gert and Olry, Annie and Parker, Samantha and Paschall, Justin and Philippakis, Anthony A and Rehm, Heidi L and Robinson, Peter N and Sham, Pak-Chung and Stefanov, Rumen and Taruscio, Domenica and Unni, Divya and Vanstone, Megan R and Zhang, Feng and Brunner, Han and Bamshad, Michael J and Lochm{\"u}ller, Hanns}
}
@article {310,
	title = {PhenoDB: a new web-based tool for the collection, storage, and analysis of phenotypic features.},
	journal = {Hum Mutat},
	volume = {34},
	year = {2013},
	month = {2013 Apr},
	pages = {566-71},
	abstract = {<p>To interpret whole exome/genome sequence data for clinical and research purposes, comprehensive phenotypic information, knowledge of pedigree structure, and results of previous clinical testing are essential. With these requirements in mind and to meet the needs of the Centers for Mendelian Genomics project, we have developed PhenoDB (http://phenodb.net), a secure, Web-based portal for entry, storage, and analysis of phenotypic and other clinical information. The phenotypic features are organized hierarchically according to the major headings and subheadings of the Online Mendelian Inheritance in Man (OMIM{\textregistered}) clinical synopses, with further subdivisions according to structure and function. Every string allows for a free-text entry. All of the approximately 2,900 features use the preferred term from Elements of Morphology and are fully searchable and mapped to the Human Phenotype Ontology and Elements of Morphology. The PhenoDB allows for ascertainment of relevant information from a case in a family or cohort, which is then searchable by family, OMIM number, phenotypic feature, mode of inheritance, genes screened, and so on. The database can also be used to format phenotypic data for submission to dbGaP for appropriately consented individuals. PhenoDB was built using Django, an open source Web development tool, and is freely available through the Johns Hopkins McKusick-Nathans Institute of Genetic Medicine (http://phenodb.net).</p>},
	keywords = {Databases, Factual, Genomics, Humans, Internet, Medical Informatics, Phenotype, Software},
	issn = {1098-1004},
	doi = {10.1002/humu.22283},
	author = {Hamosh, Ada and Sobreira, Nara and Hoover-Fong, Julie and Sutton, V Reid and Boehm, Corinne and Schiettecatte, Fran{\c c}ois and Valle, David}
}
