Set up successful AI initiatives and accelerate scientific outcomes using harmonized biomedical data on Polly.
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Leverage our ML expertise to build and deploy proprietary ML models on multi-omics data for a variety of use cases like target identification, biomarker discovery, cell type annotation, and patient stratification.
Our experts gather your analysis and data requirements, develop relevant training datasets and models, train the model, and deploy it to generate robust predictions.
Transform all your data into consistently processed, annotated, and interoperable formats with Polly's harmonization engine.
Run queries across these harmonized multi-modal and multi-source data using PollyGPT, a powerful natural language-based querying interface.
Unlock efficient data retrieval and downstream analyses (heatmaps, gene expression analysis, signature extraction, gene-target associations etc). By querying across harmonized data, at the study, sample, feature, and data matrix levels.
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Work with our experts to deploy popular foundational models like scGPT across your own harmonized data. Perform downstream tasks like cell type annotation, batch effect correction, and more.
Fine-tune generative models with task-specific harmonized data to improve prediction accuracy and unlock a range of downstream applications.
Develop foundational models using high-quality, ML-ready data processed at high throughput (TBs of data) from public or in-house sources.
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