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OpenDrop a modular, open source digital microfludics platform for research purposes. The device uses recent electro-wetting technology to control small droplets of liquids. Potential applications are lab on a chip devices for automating processes of digital biology.

Stytra, a flexible, open-source software package, written in Python and designed to cover all the general requirements involved in larval zebrafish behavioral experiments. It provides timed stimulus presentation, interfacing with external devices and simultaneous real-time tracking of behavioral parameters such as position, orientation, tail and eye motion in both freely-swimming and head-restrained preparations.

Researchers in the biomedical area are always involved in methodologies comprising several processes that are repetitive and time-consuming; these researchers can take advantage of this time for other more important things.

A free and open platform for sharing MRI, MEG, EEG, iEEG, and ECoG data. With OpenNeuro, you can: Browse and explore public datasets and analyses from a wide range of global contributors.

The project overall aim is to provide cost efficient solution to drive microfluidics systems for e.g. cell culture and organ on a chip applications. Pumps, valves and other accessories are ofter expensive to buy or very expensive to custom made.

Organ on a chip is typically difficult to achieve due to large technical challenges such as fabrication of chips and systems and biological challenges such as co-culture of cells. In this project we have developed a system to stack 12 well plates inserts on top of each other where each plate holds a tissue.

cellfinder is software from the Margrie Lab at the Sainsbury Wellcome Centre for automated 3D cell detection and registration of whole-brain images (e.g. serial two-photon or lightsheet imaging). It’s a work in progress, but cellfinder can:

DeepLabCut™ is an efficient method for 3D markerless pose estimation based on transfer learning with deep neural networks that achieves excellent results (i.e. you can match human labeling accuracy) with minimal training data (typically 50-200 frames).

Nilearn is a Python module for fast and easy statistical learning on NeuroImaging data. It leverages the scikit-learn Python toolbox for multivariate statistics with applications such as predictive modelling, classification, decoding, or connectivity analysis.

The fruit fly, Drosophila melanogaster, continues to be one of the most widely used model organisms in biomedical research. Though chosen for its ease of husbandry, maintaining large numbers of stocks of fruit flies, as done by many laboratories, is labour-intensive.