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Polly delivers curated biomedical data to expedite research outcomes.
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Get access to relevant biomedical studies from your preferred public sources. Connect public data with proprietary findings for a complete view of disease biology.
Our experts predict your data needs and deliver studies tailored to your biological question
All datasets are provided in a QC-ed, processed & metadata annotated format on Polly
Harmonize large amounts of public or proprietary biomedical data through Polly’s NLP-driven curation process. Make all your data comparable, interoperable and ML-ready.
Orchestrate end-to-end data processing (quality control, normalization, alignment) with customizable pipelines on Polly
Integrate normalized data with ontology backed metadata to fit unique analysis needs
Cut down time spent on data wrangling and jump straight to analysis using an actionable, curated set of biomedical datasets.
Investigate studies at the dataset, sample and feature levels through code or simple visualization tools
Seamlessly integrate Polly’s curated data into your existing analytical setup with APIs
Avoid off-the-mark predictions by fuelling ML models with clean, linked and high quality omics data.
Match indications to targets 75% faster using high quality omics datasets on Polly.
Save 2000 hours per year on data wrangling. Let Polly handle data preparation while your scientists focus on higher-value research.
Polly is being utilized by multiple biopharma partners to convert TBs of public or in-house data into 'ML-Ready' formats. The platform employs an NLP-assisted curation engine to rapidly impute metadata, process data consistently and engineer to a verified data model.
biomedical datasets curated
unique biological data types transformed
accuracy for study, sample and feature level curation
times as much metadata after curation
Use Polly’s signature database to identify indications related to a gene signature, or find drugs that reverse a disease signature.
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Predict diagnostic or prognostic biomarkers by analyzing Bulk RNA-seq Samples from Polly.
Integrate gene expression studies to identify target genes or enriched pathways in a selected indication.
Train ML classifiers on curated RNA-seq data to accurately segment patient cohorts for a specific indication.
Identify, extract, and annotate cell types or subtypes from single-cell datasets using a custom marker list.
Analyze, visualize, and collaborate on data using interactive dashboards for in-depth exploration and insights.
Work with our experts to build data processing pipelines customized to your data and analysis requirements.
Build, train and deploy ML models for biomarker identification, disease sub-type prediction and patient stratification.
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Explore Polly's collection of curated biomedical datasets aggregated from 10+ public sources. Datasets on Polly are consistently processed and enriched with ontology backed metadata, making them queryable and analysis-ready.
Find relevant datasets within minutes using rich metadata annotations and supplementary scientific information. Run cross study, source and omics type queries on semantically aligned biomedical datasets.
Cut down time spent on data wrangling and jump straight to analysis using an actionable, curated set of biomedical datasets. Request deeper curation to capture rich metadata and relationships between samples, features and other biomedical entities.
Improve research velocity with access to curated biomedical data on Polly
Discover targets 75% faster using high quality biomedical datasets from Polly. Perform more robust analysis and match indications to targets faster.
Don't lose weeks of your research time to data wrangling. Free atleast 1700 hours per study with access to consisently processed datasets from Polly.
Realise insights from over 43,000 deeply curated single cell and Bulk RNA-Seq datasets spanning a wide sprectrum of disease areas.
Rich metadata annotations help you infer the entire experiment design over an intuitive UI (sample descriptors, volume of cells, donor information).
Dataset, sample, and feature level metadata are harmonized with consistent ontologies to enable cross-study, source, and data type queries.
Discover related datasets easily using underlying connections in the metadata powered by knowledge graphs and ontology mapping.
Analyze and visualize data to extract insights using tools and integrations on the platform.
Run complex queries and connect results to your pipeline using API and libraries.
Let your experts focus on high value tasks like insight generation rather than data cleaning.
Ingest, curate & prepare the data for AI/ML applications with centralized control.
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