Share this on:. Wilbert van Panhuis, M. Those tweets spurred a scramble for his team at the University of Pittsburgh to establish a platform for research collaborations and data sharing on what would become the COVID pandemic. Immediately, the researchers started to compile datasets and early research publications into a central COVID repository for the scientific community, and last week, they launched the online portal for COVID modeling research — a clearinghouse for sharing data-driven discoveries about COVID These numbers are growing every day. Many of the MIDAS members are conducting modeling research on COVID and are contributing to an extraordinary international collection of data and information regarding the outbreak. A completely new research culture has emerged during this outbreak. One aspect is rapid sharing of data and model results by community members. During past outbreaks for diseases such as Ebola, individual MIDAS researchers have taken on the role of facilitating connections between scientists, data sources and public health officials. The wealth of data and information emerging from the scientific and public health community can be difficult to navigate, and various reports about confusion regarding data provenance and comparability have emerged in the news and social media.
A Genetic Data Matchmaking Service for Researchers
Human Mutation, — The Matchmaker Exchange application programming interface API allows searching a patient’s genotypic or phenotypic profiles across clinical sites, for the purposes of cohort discovery and variant disease causal validation. This API can be used not only to search for matching patients, but also to match against public disease and model organism data. This public disease data enable matching known diseases and variant-phenotype associations using phenotype semantic similarity algorithms developed by the Monarch Initiative.
The model data can provide additional evidence to aid diagnosis, suggest relevant models for disease mechanism and treatment exploration, and identify collaborators across the translational divide.
Matchmaker Exchange platform for rare disease gene discovery. Bristena Oprisanu* and Emiliano De Cristofaro. Department of Computer Science, University.
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John T. However, serendipity has never proven to be a reliable or scalable approach in science. As such, the Matchmaker Exchange MME was launched to provide a robust and systematic approach to rare disease gene discovery through the creation of a federated network connecting databases of genotypes and rare phenotypes using a common application programming interface API. The core building blocks of the MME have been defined and assembled.
Additional databases that support internal matching are anticipated to join the MME network as it continues to grow.
Discovering new diseases with the internet: How to find a matching patient. [article index] Gene names are the most important for Internet-based matchmaking.
In both research and clinical settings, the majority of patients with rare disease lack a clear etiology after exome and genome sequencing. Finding just a single additional case with a deleterious variant in the same gene and overlapping phenotype may provide sufficient evidence to identify the causative gene, but today, case data sits in isolated databases. The ‘Matchmaker Exchange’ project was launched in October to address this challenge and find genetic causes for patients with rare disease.
This involves a large and growing number of teams and projects working towards a federated platform Exchange to facilitate the matching of cases with similar phenotypic and genotypic profiles matchmaking through standardized application programming interfaces APIs and procedural conventions. Toggle navigation Home Matchmaker Exchange. The Challenge In both research and clinical settings, the majority of patients with rare disease lack a clear etiology after exome and genome sequencing.
The Solution The ‘Matchmaker Exchange’ project was launched in October to address this challenge and find genetic causes for patients with rare disease.
Daughter’s Diagnosis Inspires Mom to Create Health Matchmaking Service
New technologies are already enabling the deployment of health services to remote areas and helping patients navigate health systems, allowing them more visibility on care cost and quality, among other things. Reducing the risk of investing in these markets is one of the objectives of TechEmerge Health, an IFC program that connects tech companies worldwide with leading health-care providers in emerging markets.
IFC is calling on innovators from around the world to apply for the program, which will match their tech innovations with health facilities in East Africa. Applications are being accepted for the next six weeks, through February TechEmerge is being implemented in partnership with the governments of Finland and Israel.
Calling the most innovative organisations in Europe: Matchmaking Health Promotion & Prevention of Age Related Frailty and Disease.
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Patient A:II-1 was born in the Netherlands three weeks early with short, flattened bones in her upper body. She seemed otherwise healthy until her horseshoe-shaped kidneys began to fail. She developed an increasing need for oxygen and died within seven weeks. Without any clues as to the origin of her disorder, her clinicians submitted her case for whole exome sequencing and candidate causes of her disease e.
Find a colleague who has seen a similar case and compare notes. Before the days of spit vials and cheek swabs, before the days of the Internet and APIs application programming interfaces , this work was not easy.
And for patients with advanced disease, missed opportunities for enrollment means a missed chance for treatment. Vassiliki Papadimitrakopoulou.
The Matchmaker Exchange application programming interface API allows searching a patient’s genotypic or phenotypic profiles across clinical sites, for the purposes of cohort discovery and variant disease causal validation. This API can be used not only to search for matching patients, but also to match against public disease and model organism data. This public disease data enable matching known diseases and variant-phenotype associations using phenotype semantic similarity algorithms developed by the Monarch Initiative.
The model data can provide additional evidence to aid diagnosis, suggest relevant models for disease mechanism and treatment exploration, and identify collaborators across the translational divide. The Monarch Initiative provides an implementation of this API for searching multiple integrated sources of data that contextualize the knowledge about any given patient or patient family into the greater biomedical knowledge landscape. While this corpus of data can aid diagnosis, it is also the beginning of research to improve understanding of rare human diseases.
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The undiagnosed diseases program: Approach to diagnosis
Everyone knows the beginning of the age of industrialization in England was not pleasant. People looking for work crowded into cities, which then became cesspools of disease and pollution. One particularly dirty job done by women and children actually made them glow in the dark: matchstick making. Recently, anthropologists studying the skeleton of a young teenager discovered that the bones appear to show the physical hallmarks of phosphorus poisoning, among other conditions.
Phossy jaw, formally known as phosphorus necrosis of the jaw, was an occupational disease “Matchmakers’ “phossy jaw” eradicated”. American Industrial.
Rare congenital disorder discovered through genetic matchmaking
Children with congenital disorders of glycosylation may suffer from epilepsy, developmental delay, autistic features, decreased stature and chronic insomnia. However, children are often misdiagnosed, since these disorders are rare or unknown. For the parents of these children, the uncertainty about what is wrong with their child can be almost unbearable. We had a really hard time figuring out what was wrong with these children.
At the same time, we are many in epidemiology who neither work clinically nor do research specifically on infectious diseases, and are.
This article is only available in the PDF format. Download the PDF to view the article, as well as its associated figures and tables. The program was born of despair after an ultra-Orthodox Jewish rabbi in New York realized that his once-healthy infant daughter had Tay-Sachs disease. She would be the fourth of his children to die of the genetic disorder. Like the others, she would suffer progressive neurological deterioration.
She would become severely mentally retarded, lose her vision and motor control, have cerebral seizures, and, probably before her sixth birthday, die. To make matters worse, the rabbi knew that his family might not have seen the last of Tay-Sachs. Both he and his wife carried a recessive allele for the disease, so chances were one in four that any additional offspring would be affected.
Moreover, ultra-Orthodox law proscribed abortion; contraception is permitted only under certain conditions. Merz B. Coronavirus Resource Center.