Orphanet et son réseau : où trouver une information validée sur les maladies rares

Maiella, Sylvie; Rath, Ana; Angin, Cem; Mousson, F.; Kremp, O.

doi:10.1016/s0035-3787(13)70052-3

Cited by 39 publications

(27 citation statements)

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“…(ii) DO symptoms (12), using the ‘has_symptom’ relationship. (iii) Orphanet (13) clinical signs. Recently, Orphanet has added HPO terminology, and this will be shown in MalaCards 1.12, assisting future unification.…”

Section: Annotationsmentioning

confidence: 99%

MalaCards: an amalgamated human disease compendium with diverse clinical and genetic annotation and structured search

et al. 2016

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The MalaCards human disease database (http://www.malacards.org/) is an integrated compendium of annotated diseases mined from 68 data sources. MalaCards has a web card for each of ∼20 000 disease entries, in six global categories. It portrays a broad array of annotation topics in 15 sections, including Summaries, Symptoms, Anatomical Context, Drugs, Genetic Tests, Variations and Publications. The Aliases and Classifications section reflects an algorithm for disease name integration across often-conflicting sources, providing effective annotation consolidation. A central feature is a balanced Genes section, with scores reflecting the strength of disease-gene associations. This is accompanied by other gene-related disease information such as pathways, mouse phenotypes and GO-terms, stemming from MalaCards’ affiliation with the GeneCards Suite of databases. MalaCards’ capacity to inter-link information from complementary sources, along with its elaborate search function, relational database infrastructure and convenient data dumps, allows it to tackle its rich disease annotation landscape, and facilitates systems analyses and genome sequence interpretation. MalaCards adopts a ‘flat’ disease-card approach, but each card is mapped to popular hierarchical ontologies (e.g. International Classification of Diseases, Human Phenotype Ontology and Unified Medical Language System) and also contains information about multi-level relations among diseases, thereby providing an optimal tool for disease representation and scrutiny.

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Section: Annotationsmentioning

confidence: 99%

MalaCards: an amalgamated human disease compendium with diverse clinical and genetic annotation and structured search

et al. 2016

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“…Daily data mining and integration processes have been developed to maintain the “nonhuman” agents (more than 63,000 human genes and 14,000 genetic diseases) up to date and generate a news flow (more than 1 million news items were created in the last year) by exploiting public (Ensembl [37], NCBI, Uniprot [12], HPO [45], OMIM [10], Orphanet [56], OrthoInspector [42], etc) and in-house data resources. All data retrieved or processed by MyGeneFriends and related to genes and diseases are “public,” whereas data submitted by humans are “private” (visible only by the owner) by default, unless the human decides to make it “protected” (visible by owner and selected collaborators) or “public” (visible to anyone).…”

Section: Resultsmentioning

confidence: 99%

MyGeneFriends: A Social Network Linking Genes, Genetic Diseases, and Researchers

et al. 2017

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BackgroundThe constant and massive increase of biological data offers unprecedented opportunities to decipher the function and evolution of genes and their roles in human diseases. However, the multiplicity of sources and flow of data mean that efficient access to useful information and knowledge production has become a major challenge. This challenge can be addressed by taking inspiration from Web 2.0 and particularly social networks, which are at the forefront of big data exploration and human-data interaction.ObjectiveMyGeneFriends is a Web platform inspired by social networks, devoted to genetic disease analysis, and organized around three types of proactive agents: genes, humans, and genetic diseases. The aim of this study was to improve exploration and exploitation of biological, postgenomic era big data.MethodsMyGeneFriends leverages conventions popularized by top social networks (Facebook, LinkedIn, etc), such as networks of friends, profile pages, friendship recommendations, affinity scores, news feeds, content recommendation, and data visualization.ResultsMyGeneFriends provides simple and intuitive interactions with data through evaluation and visualization of connections (friendships) between genes, humans, and diseases. The platform suggests new friends and publications and allows agents to follow the activity of their friends. It dynamically personalizes information depending on the user’s specific interests and provides an efficient way to share information with collaborators. Furthermore, the user’s behavior itself generates new information that constitutes an added value integrated in the network, which can be used to discover new connections between biological agents.ConclusionsWe have developed MyGeneFriends, a Web platform leveraging conventions from popular social networks to redefine the relationship between humans and biological big data and improve human processing of biomedical data. MyGeneFriends is available at lbgi.fr/mygenefriends.

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“…The results from this study can be integrated with other rare disease research platforms like RD-Connect [28] and Orphanet [29–31] to further collaborations across disciplines and institutes.…”

Section: Discussionmentioning

confidence: 99%

Opportunities for developing therapies for rare genetic diseases: focus on gain-of-function and allostery

Chen

Altman

2017

Orphanet J Rare Dis

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BackgroundAdvances in next generation sequencing technologies have revolutionized our ability to discover the causes of rare genetic diseases. However, developing treatments for these diseases remains challenging. In fact, when we systematically analyze the US FDA orphan drug list, we find that only 8% of rare diseases have an FDA-designated drug. Our approach leverages three primary insights: first, diseases with gain-of-function mutations and late onset are more likely to have drug options; second, drugs are more often inhibitors than activators; and third, some disease-causing proteins can be rescued by allosteric activators in diseases due to loss-of-function mutations.ResultsWe have developed a pipeline that combines natural language processing and human curation to mine promising targets for drug development from the Online Mendelian Inheritance in Man (OMIM) database. This pipeline targets diseases caused by well-characterized gain-of-function mutations or loss-of-function proteins with known allosteric activators. Applying this pipeline across thousands of rare genetic diseases, we discover 34 rare genetic diseases that are promising candidates for drug development.ConclusionOur analysis has revealed uneven coverage of rare diseases in the current US FDA orphan drug space. Diseases with gain-of-function mutations or loss-of-function mutations and known allosteric activators should be prioritized for drug treatments.Electronic supplementary materialThe online version of this article (doi:10.1186/s13023-017-0614-4) contains supplementary material, which is available to authorized users.

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Orphanet et son réseau : où trouver une information validée sur les maladies rares

Cited by 39 publications

References 1 publication

MalaCards: an amalgamated human disease compendium with diverse clinical and genetic annotation and structured search

MalaCards: an amalgamated human disease compendium with diverse clinical and genetic annotation and structured search

MyGeneFriends: A Social Network Linking Genes, Genetic Diseases, and Researchers

Opportunities for developing therapies for rare genetic diseases: focus on gain-of-function and allostery

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