SwePub
Sök i SwePub databas

  Extended search

Träfflista för sökning "WFRF:(Licata Luana) "

Search: WFRF:(Licata Luana)

  • Result 1-2 of 2
Sort/group result
   
EnumerationReferenceCoverFind
1.
  • Laurie, Steven, et al. (author)
  • The RD-Connect Genome-Phenome Analysis Platform : Accelerating diagnosis, research, and gene discovery for rare diseases
  • 2022
  • In: Human Mutation. - : John Wiley & Sons. - 1059-7794 .- 1098-1004. ; 43:6, s. 717-733
  • Journal article (peer-reviewed)abstract
    • Rare disease patients are more likely to receive a rapid molecular diagnosis nowadays thanks to the wide adoption of next-generation sequencing. However, many cases remain undiagnosed even after exome or genome analysis, because the methods used missed the molecular cause in a known gene, or a novel causative gene could not be identified and/or confirmed. To address these challenges, the RD-Connect Genome-Phenome Analysis Platform (GPAP) facilitates the collation, discovery, sharing, and analysis of standardized genome-phenome data within a collaborative environment. Authorized clinicians and researchers submit pseudonymised phenotypic profiles encoded using the Human Phenotype Ontology, and raw genomic data which is processed through a standardized pipeline. After an optional embargo period, the data are shared with other platform users, with the objective that similar cases in the system and queries from peers may help diagnose the case. Additionally, the platform enables bidirectional discovery of similar cases in other databases from the Matchmaker Exchange network. To facilitate genome-phenome analysis and interpretation by clinical researchers, the RD-Connect GPAP provides a powerful user-friendly interface and leverages tens of information sources. As a result, the resource has already helped diagnose hundreds of rare disease patients and discover new disease causing genes.
  •  
2.
  • Ostaszewski, Marek, et al. (author)
  • COVID19 Disease Map, a computational knowledge repository of virus-host interaction mechanisms
  • 2021
  • In: Molecular Systems Biology. - : John Wiley & Sons. - 1744-4292 .- 1744-4292. ; 17:10
  • Journal article (peer-reviewed)abstract
    • We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph-based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, bioinformaticians and computational biologists. The diagrams of the C19DMap, curated from the literature, are integrated with relevant interaction and text mining databases. We demonstrate the application of network analysis and modelling approaches by concrete examples to highlight new testable hypotheses. This framework helps to find signatures of SARS-CoV-2 predisposition, treatment response or prioritisation of drug candidates. Such an approach may help deal with new waves of COVID-19 or similar pandemics in the long-term perspective.
  •  
Skapa referenser, mejla, bekava och länka
  • Result 1-2 of 2

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

 
pil uppåt Close

Copy and save the link in order to return to this view