Explore projects
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rhaase / ABIA_Prague_2019
Creative Commons Attribution Non Commercial 4.0 InternationalUpdated -
walker / cellpose_explore
BSD 3-Clause "New" or "Revised" LicenseExploring cellpose (deep learning) for segmentation in 2D&3D. Including setup for GPU on cluster or workstation
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dibrov / chromosome_size
MIT LicenseUpdated -
Improving contrast in confocal data by degrading image with model of light scattering
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kramer / cycle-coalescence-algorithm
MIT LicenseThis is a python implementation of the cycle coalescence algorithm as described by Modes et al, 2016.
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rost / devcontainer-example
BSD 3-Clause "New" or "Revised" LicenseUpdated -
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This repository is all about simulating flow driven pruning in biological flow networks.
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Mateus_Group / Guanine_crystal_analysis_APOC
BSD 3-Clause "New" or "Revised" LicenseRepository of Code used in the Bachelor Thesis "Guanine crystal segmentation and classification imaged in the eye of zebrafish embryos"
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Sequencing analysis pipeline for our paper "Human liver cholangiocyte organoids capture the heterogeneity of in vivo liver ductal epithelium"
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Repository containing the scripts used in Iglesias-Artola et al 2024. Quantitative imaging of species-specific lipid transport in mammalian cells
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Huch lab / Image Analysis Pipelines - Mouse liver assembloids model periportal architecture and biliary fibrosis
BSD 3-Clause "New" or "Revised" LicenseThis repository contains the image analysis pipelines for bile canaliculi analysis and mesenchyme counting associated with the paper "Mouse liver assembloids model periportal architecture and biliary fibrosis"
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Veenvliet Lab / Integrated_Molecular-Phenotypic_Profiling_of_Stembryos
BSD 3-Clause "New" or "Revised" LicenseThis is a code-repository for the image-, sequencing and data-analysis performed for the manuscript: Integrated Molecular-Phenotypic Profiling Reveals Tuneable Modulators of Morphological Variation in Stembryos" authored by: Alba Villaronga Luque et al.
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rhaase / int_sys_2020
Creative Commons Attribution Non Commercial 4.0 InternationalUpdated -
Code accompanying "Inverse-Dirichlet Weighting Enables Reliable Training of Physics Informed Neural Networks", Maddu et al., 2021
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