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Bioregistry, biologic entity registration

Register your biologic entities in the bioregistry to centralize and explore data relationships.

Biologics LIMS includes a bioregistry to capture complete entity and sample information during the biologics development process. Biological entity registration allows scientists to easily find, view and navigate through entities, their lineage and data relationships. For example, using the bioregistry scientists can easily find a specific protein sequence and see all the molecules, samples and assay data connected to that sequence.

Registering entities with Biologics LIMS allows you to:

  • Improve data integrity using a central bioregistry to register sequences, cell lines, molecules, expression systems, vectors, constructs and more.
  • Gain insight from interrogating lineage and data relationships between samples and registered entities.
  • Capture structured data and automatically build data relationships to support complex queries and data-driven decision-making.
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Easily register biological entities and explore their data relationships.

Register all biological and molecular entities in the bioregistry.

  • Supports registration of molecules, nucleotide sequences, protein sequences, expression systems, constructs, vectors and cell lines.
  • Register entities individually using the registration wizard, bulk upload via .csv or Excel file and via the LabKey API.
  • Checked entities for uniqueness during registration and assign unique entity ID using any of these methods.

Automatically build and navigate entity relationships for faster decision-making.

  • Capture structured data for bioregistry entities and samples.
  • Customize and edit the characteristics of bioregistry entities, add new entities and adjust/define the relationships between them.
  • Automatically build essential data relationships between entities.

Connect your molecular entities to samples and related biologics R&D data.

  • Automatically connect samples to their molecular components, allowing teams to explore complex data relationships.
  • Track the complete lineage of samples allowing the analysis of experimental results through many generations of derivation.
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