Biological databases are notorious for poor data standards, and public single cell data is no exception.
The issues can be many: Lack of standards for cell-level metadata deposition, variable data processing pipelines or missing cell annotations.
In this webinar, our experts dive into these challenges and lessons learned while curating public single cell studies.
What You’ll Learn:
Biological databases are notorious for poor data standards, and public single cell data is no exception.
The issues can be many: Lack of standards for cell-level metadata deposition, variable data processing pipelines or missing cell annotations.
In this webinar, our experts dive into these challenges and lessons learned while curating public single cell studies.
What You’ll Learn:
Scaling clinico-genomic data integration: Large pharmaceutical organizations working with external data providers used Polly to build interoperable clinico-genomic data products 6x faster.
Although purchased datasets are often labeled as "clean," they still lack interoperability—Polly's pipelines bridge this gap with robust integration and harmonization.
Information Retrieval: Drug safety monitoring teams used Polly's Knowledge Graph powered co-scientist to conversationally retrieve the right cohorts & assess drug response—cutting discovery time by 70%.
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If you’re working with complex biological data, you may be asking:
Can generative AI truly assist in scientific reasoning, not just data analysis?
What does it mean for hypothesis generation, literature review, or even designing experiments?
Could this accelerate—not replace—my discovery pipeline?
Whether you're skeptical, curious, or already experimenting with AI in your lab—this is a session designed to ground your understanding in evidence, not speculation.
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