ArticleBehavior research methods2018
PyMICE: APython library for analysis of IntelliCage data.
Article in Behavior research methods, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
4 citing papers in PubMed.
- A comprehensive and standardized pipeline for automated profiling of higher cognition in mice.Cell reports methods · 2025Article
- IntelliCage: the development and perspectives of a mouse- and user-friendly automated behavioral test system.Frontiers in behavioral neuroscience · 2023Review
- PSD-95 in CA1 Area Regulates Spatial Choice Depending on Age.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2021Article
- Automated, Long-term Behavioral Assay for Cognitive Functions in Multiple Genetic Models of Alzheimer's Disease, Using IntelliCage.Journal of visualized experiments : JoVE · 2018Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
IntelliCage is an automated system for recording the behavior of a group of mice housed together. It produces rich, detailed behavioral data calling for new methods and software for their analysis. Here we present PyMICE, a free and open-source library for analysis of IntelliCage data in the Python programming language. We describe the design and demonstrate the use of the library through a series of examples. PyMICE provides easy and intuitive access to IntelliCage data, and thus facilitates the possibility of using numerous other Python scientific libraries to form a complete data analysis workflow.
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Registered trials
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