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RD-Connect: An Integrated Platform Connecting Databases, Registries, Biobanks and Clinical Bioinformatics for Rare Disease Research

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TLDR
RD-Connect is a global infrastructure project initiated in November 2012 that links genomic data with registries, biobanks, and clinical bioinformatics tools to produce a central research resource for rare diseases.
Abstract
Research into rare diseases is typically fragmented by data type and disease Individual efforts often have poor interoperability and do not systematically connect data across clinical phenotype, genomic data, biomaterial availability, and research/trial data sets Such data must be linked at both an individual-patient and whole-cohort level to enable researchers to gain a complete view of their disease and patient population of interest Data access and authorization procedures are required to allow researchers in multiple institutions to securely compare results and gain new insights Funded by the European Union's Seventh Framework Programme under the International Rare Diseases Research Consortium (IRDiRC), RD-Connect is a global infrastructure project initiated in November 2012 that links genomic data with registries, biobanks, and clinical bioinformatics tools to produce a central research resource for rare diseases

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The Human Phenotype Ontology in 2017

Sebastian Köhler, +60 more
TL;DR: The progress of the HPO project is reviewed, including specific areas of expansion such as common (complex) disease, new algorithms for phenotype driven genomic discovery and diagnostics, integration of cross-species mapping efforts with the Mammalian Phenotype Ontology, an improved quality control pipeline, and the addition of patient-friendly terminology.
Journal ArticleDOI

Expansion of the Human Phenotype Ontology (HPO) knowledge base and resources

Sebastian Köhler, +69 more
TL;DR: The HPO’s interoperability with other ontologies has enabled it to be used to improve diagnostic accuracy by incorporating model organism data and plays a key role in the popular Exomiser tool, which identifies potential disease-causing variants from whole-exome or whole-genome sequencing data.
Journal ArticleDOI

Exploiting machine learning for end-to-end drug discovery and development

TL;DR: The application of machine learning models in the design, synthesis and characterisation of molecules at different stages in the drug discovery and development process has considerable implications for developing future therapies and their targeting.
Journal ArticleDOI

International Cooperation to Enable the Diagnosis of All Rare Genetic Diseases.

TL;DR: The current and future bottlenecks to gene discovery are reviewed and strategies for enabling progress are suggested for enabling precision medicine for this patient population.
Journal ArticleDOI

Computational approaches in target identification and drug discovery

TL;DR: It is felt that big data leveraging needs to be cost-effective and focus on personalized medicine and the interplay of information technologies and (chemo)informatic tools on the basis of their synergy is proposed.
References
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Journal ArticleDOI

International network of cancer genome projects

Thomas J. Hudson, +273 more
TL;DR: Systematic studies of more than 25,000 cancer genomes will reveal the repertoire of oncogenic mutations, uncover traces of the mutagenic influences, define clinically relevant subtypes for prognosis and therapeutic management, and enable the development of new cancer therapies.
Journal ArticleDOI

DECIPHER: Database of Chromosomal Imbalance and Phenotype in Humans Using Ensembl Resources

TL;DR: An interactive web-based database called DECIPHER (Database of Chromosomal Imbalance and Phenotype in Humans Using Ensembl Resources) which incorporates a suite of tools designed to aid the interpretation of submicroscopic chromosomal imbalance, inversions, and translocations.
Journal ArticleDOI

LOVD v.2.0: the next generation in gene variant databases.

TL;DR: The Leiden Open‐source Variation Database (LOVD) is described, which adds enhanced flexibility and functionality and has the capacity to store sequence variants in multiple genes per patient and the database structure supports fast queries and allows storage of sequence variants from high‐throughput sequence analysis.
Journal ArticleDOI

The Human Phenotype Ontology project: linking molecular biology and disease through phenotype data

Sebastian Köhler, +50 more
TL;DR: The updated HPO database is described, which provides annotations of 7,278 human hereditary syndromes listed in OMIM, Orphanet and DECIPHER to classes of the HPO, allowing integration of existing datasets and interoperability with multiple biomedical resources.
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