Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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Materials Map under construction

The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (1/1 displayed)

  • 2019Potential for diagnosis of infectious disease from the 100,000 Genomes Project Metagenomic Dataset: Recommendations for reporting results10citations

Places of action

Chart of shared publication
Cooper, Colin
1 / 1 shared
Jeffery, Katie
1 / 2 shared
Wallace, Susan E.
1 / 1 shared
Matthews, Philippa C.
1 / 1 shared
Lucassen, Anneke
1 / 5 shared
Magiorkinis, Gkikas
1 / 1 shared
Brewer, Daniel S.
1 / 1 shared
Gihawi, Abraham
1 / 1 shared
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Rallapalli, Ghanasyam
1 / 1 shared
Mbisa, Jean L.
1 / 1 shared
Tedder, Richard
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1 / 1 shared
Simmonds, Peter
1 / 1 shared
Fowler, Tom
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Lahnstein, Lea
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Chart of publication period
2019

Co-Authors (by relevance)

  • Cooper, Colin
  • Jeffery, Katie
  • Wallace, Susan E.
  • Matthews, Philippa C.
  • Lucassen, Anneke
  • Magiorkinis, Gkikas
  • Brewer, Daniel S.
  • Gihawi, Abraham
  • Patch, Christine
  • Rallapalli, Ghanasyam
  • Mbisa, Jean L.
  • Tedder, Richard
  • Dunbar, Kevin
  • Maleady-Crowe, Fiona
  • Simmonds, Peter
  • Fowler, Tom
  • Lahnstein, Lea
  • Vayena, Effy
OrganizationsLocationPeople

article

Potential for diagnosis of infectious disease from the 100,000 Genomes Project Metagenomic Dataset: Recommendations for reporting results

  • Cooper, Colin
  • Jeffery, Katie
  • Wallace, Susan E.
  • Matthews, Philippa C.
  • Lucassen, Anneke
  • Magiorkinis, Gkikas
  • Brewer, Daniel S.
  • Gihawi, Abraham
  • Patch, Christine
  • Rallapalli, Ghanasyam
  • Hannigan, Bernadette
  • Mbisa, Jean L.
  • Tedder, Richard
  • Dunbar, Kevin
  • Maleady-Crowe, Fiona
  • Simmonds, Peter
  • Fowler, Tom
  • Lahnstein, Lea
  • Vayena, Effy
Abstract

The identification of microbiological infection is usually a diagnostic investigation, a complex process that is firstly initiated by clinical suspicion. With the emergence of high-throughput sequencing (HTS) technologies, metagenomic analysis has unveiled the power to identify microbial DNA/RNA from a diverse range of clinical samples (1). Metagenomic analysis of whole human genomes at the clinical/research interface bypasses the steps of clinical scrutiny and targeted testing and has the potential to generate unexpected findings relating to infectious and sometimes transmissible disease. There is no doubt that microbial findings that may have a significant impact on a patient’s treatment and their close contacts should be reported to those with clinical responsibility for the sample-donating patient. There are no clear recommendations on how such findings that are incidental, or outside the original investigation, should be handled. Here we aim to provide an informed protocol for the management of incidental microbial findings as part of the 100,000 Genomes Projectwhich may have broader application in this emerging field. As with any other clinical information, we aim to prioritise the reporting of data that are most likely to be of benefit to the patient and their close contacts. We also set out to minimize risks, costs and potential anxiety associated with the reporting of results that are unlikely to be of clinical significance. Our recommendations aim to support the practice of microbial metagenomics by providing a simplified pathway that can be applied to reporting the identification of potential pathogens from metagenomic datasets. Given that the ambition for UK sequenced human genomes over the next 5 years has been set to reach 5 million and the field of metagenomics is rapidly evolving, the guidance will be regularly reviewed and will likely adapt over time as experience develops.

Topics
  • impedance spectroscopy