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Nassar2022 - Microbiome sample-material NER model

ABSTRACT: Microbiome sample-material model is a Named Entity Recognition (NER) model that identifies and annotates the material of microbiome samples in texts. This is the final model version used to annotate metagenomics publications in Europe PMC and enrich metagenomics studies in MGnify with sample-material metadata from literature. For more information, please refer to the following blogs: http://blog.europepmc.org/2020/11/europe-pmc-publications-metagenomics-annotations.html https://www.ebi.ac.uk/about/news/service-news/enriched-metadata-fields-mgnify-based-text-mining-associated-publications

SUBMITTER: Maaly Nassar  

PROVIDER: MODEL2202170001 | BioModels | 2022-02-21

REPOSITORIES: BioModels

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Publications

A machine learning framework for discovery and enrichment of metagenomics metadata from open access publications.

Nassar Maaly M   Rogers Alexander B AB   Talo' Francesco F   Sanchez Santiago S   Shafique Zunaira Z   Finn Robert D RD   McEntyre Johanna J  

GigaScience 20220801

Metagenomics is a culture-independent method for studying the microbes inhabiting a particular environment. Comparing the composition of samples (functionally/taxonomically), either from a longitudinal study or cross-sectional studies, can provide clues into how the microbiota has adapted to the environment. However, a recurring challenge, especially when comparing results between independent studies, is that key metadata about the sample and molecular methods used to extract and sequence the ge  ...[more]

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