Publications by authors named "Kjiersten Fagnan"

Increases in sequencing capacity, combined with rapid accumulation of publications and associated data resources, have increased the complexity of maintaining associations between literature and genomic data. As the volume of literature and data have exceeded the capacity of manual curation, automated approaches to maintaining and confirming associations among these resources have become necessary. Here we present the Data Citation Explorer (DCE), which discovers literature incorporating genomic data that was not formally cited.

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Article Synopsis
  • Advanced omics technologies produce a large amount of data daily, but often lack the necessary metadata, making it difficult for researchers to effectively access and utilize the data.
  • Machine learning (ML) techniques are emerging as solutions for automatically annotating these datasets, but the process of text labeling to validate this metadata remains manual and time-consuming, highlighting the need for automation.
  • This paper presents two new automated text labeling approaches aimed at improving metadata validation in environmental genomics, utilizing relationships between data sources and controlled vocabularies to enhance the efficiency and effectiveness of metadata extraction.
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The nascent field of microbiome science is transitioning from a descriptive approach of cataloging taxa and functions present in an environment to applying multi-omics methods to investigate microbiome dynamics and function. A large number of new tools and algorithms have been designed and used for very specific purposes on samples collected by individual investigators or groups. While these developments have been quite instructive, the ability to compare microbiome data generated by many groups of researchers is impeded by the lack of standardized application of bioinformatics methods.

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Microbiome samples are inherently defined by the environment in which they are found. Therefore, data that provide context and enable interpretation of measurements produced from biological samples, often referred to as metadata, are critical. Important contributions have been made in the development of community-driven metadata standards; however, these standards have not been uniformly embraced by the microbiome research community.

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