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See detailEmpowering Large Chemical Knowledge Bases for Exposomics: PubChemLite Meets MetFrag
Schymanski, Emma UL; Kondic, Todor UL; Neumann, Steffen et al

E-print/Working paper (2020)

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See detailDigital Detective Work: Connecting Cheminformatics, Mass Spectrometry and our Environment (analytica Conference)
Schymanski, Emma UL; Bolton, Evan

Scientific Conference (2020, October 20)

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See detailVirtual Podium Keynote: Compound Identification and Exposomics: DIY Databases?
Schymanski, Emma UL; Bolton, Evan; Helmus, Rick et al

Presentation (2020, April 10)

In light of recent events, many of us have been impacted by the cancellation of conferences and meetings. We are not only losing the opportunity to present our research, but a chance to connect with our ... [more ▼]

In light of recent events, many of us have been impacted by the cancellation of conferences and meetings. We are not only losing the opportunity to present our research, but a chance to connect with our community. Virtual Podium is a platform and opportunity to present and learn about compelling scientific research. Our third session will be focused on Compound Identification. Our keynote speaker this week will be Emma Schymanski who is the PI of Environmental Cheminformatics at the University of Luxembourg. Session 3: Compound Identification Friday, April 10, 2020 at 12:00-1:00PM PDT (3:00-4:00PM EDT) Session 3 - Compound Identification: https://www.eventbrite.com/e/101426613732 [less ▲]

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See detailPubChemLite for Exposomics
Bolton, Evan; Schymanski, Emma UL; Kondic, Todor UL et al

Computer development (2020)

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See detailDisease Ontology 2015 update: an expanded and updated database of human diseases for linking biomedical knowledge through disease data.
Kibbe, Warren A.; Arze, Cesar; Felix, Victor et al

in Nucleic Acids Research (2015), 43(Database issue), 1071-8

The current version of the Human Disease Ontology (DO) (http://www.disease-ontology.org) database expands the utility of the ontology for the examination and comparison of genetic variation, phenotype ... [more ▼]

The current version of the Human Disease Ontology (DO) (http://www.disease-ontology.org) database expands the utility of the ontology for the examination and comparison of genetic variation, phenotype, protein, drug and epitope data through the lens of human disease. DO is a biomedical resource of standardized common and rare disease concepts with stable identifiers organized by disease etiology. The content of DO has had 192 revisions since 2012, including the addition of 760 terms. Thirty-two percent of all terms now include definitions. DO has expanded the number and diversity of research communities and community members by 50+ during the past two years. These community members actively submit term requests, coordinate biomedical resource disease representation and provide expert curation guidance. Since the DO 2012 NAR paper, there have been hundreds of term requests and a steady increase in the number of DO listserv members, twitter followers and DO website usage. DO is moving to a multi-editor model utilizing Protege to curate DO in web ontology language. This will enable closer collaboration with the Human Phenotype Ontology, EBI's Ontology Working Group, Mouse Genome Informatics and the Monarch Initiative among others, and enhance DO's current asserted view and multiple inferred views through reasoning. [less ▲]

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