Microscopy · biohub
DynaCLR-data
Live-cell microscopy time-series dataset with infection labels for dynamic contrastive cell embedding learning.
What DynaCLR-data is
DynaCLR-data is a biological and medical microscopy dataset released by biohub. It contains live-cell microscopy time series paired with infection-status labels.
The dataset serves as training and evaluation data for DynaCLR, a method focused on dynamic contrastive learning of cell embeddings from time-lapse cellular imaging.
Key facts
- Category
- Microscopy
- Fields
- Biology, medicine
- Data type
- Live-cell microscopy time series
- Labels
- Infection status
What you can use it for
- Cell embedding pre-training
- Train dynamic contrastive learning models on live-cell microscopy time series to generate cellular feature representations.
- Infection state classification
- Evaluate machine learning models on detecting or tracking cellular infection status over time.
- Representation benchmarking
- Benchmark dynamic representation learning algorithms on time-series microscopy data.
Explore the data
The schema, real rows — read in your browser, nothing downloaded.
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Strengths and limits
Good at
- Provides time-lapse live-cell microscopy sequences for learning dynamic cell representations.
- Includes infection-status annotations alongside imaging data for supervised evaluation.
Questions
Can I look inside DynaCLR-data without downloading it?
Yes. This page reads its schema, real rows and per-column statistics in the browser. Nothing is downloaded to your machine.
What licence is DynaCLR-data under?
Its authors declare bsd-3-clause. Read the terms on the original page before reusing the data.
What type of data is contained in DynaCLR-data?
The dataset contains live-cell microscopy time series alongside infection-status labels.
What was DynaCLR-data designed for?
It was curated as training and evaluation data for DynaCLR, a dynamic contrastive learning method for learning cell embeddings.
Which research fields does the dataset cover?
The dataset covers the fields of biology and medicine, with a focus on microscopy.
Written from DynaCLR-data's own dataset card. Statements citing a figure that does not appear there are removed before publication. Licence and running details come from our registry.