OmixAtlas is a collection of datasets from public, proprietary and licensed sources. Adopt an integrated approach with access to ML-ready biology-centric data to understand human physiology and disease pathology.
Build machine learning algorithms faster using analysis-ready data from an OmixAtlas. Polly's NLP based curation models map critical metadata to datasets at human level accuracy.
Perform integrative analysis with powerful code-based querying across the OmixAtlas data catalog. Explore data in-depth through code using Polly Libraries, or through contextual filters on a user-friendly UI.
Stream ML-ready data to a computational infrastructure of your choice using Polly Libraries. Focus on analysis while OmixAtlas takes care of data storage and management.
Harmonize and store data spread across proprietary databases or publications in a centralized repository. OmixAtlas consolidates data sourced from heterogeneous systems that do not "talk" to each other, breaking data silos in the organization.
Overcome challenges associated with querying across samples and features distributed in heterogeneous syst. Organizations have access to data enriched with contextual metadata, that can be reused across teams to save resources and accelerate discovery.
Standardize and harmonize existing enterprise data to reduce the time spent on processing datasets. Consume ML-ready data for developing machine learning algorithms and performing analyses.
Prevent information overload in biomedical research by scaling storage and processes to accommodate interconnected data in OmixAtlas. Process files of large sizes and volumes harmonized with the scalable curation infrastructure of Polly.