Explore projects
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miet / miet
MIT LicenseAn R package for specifying and extracting data frames ready for data analysis from populations of MR images.
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metapart / starpart
GNU General Public License v3.0 onlyFlexible and extensible framework that integrates state-of-the-art methods for graph partitioning and sparse matrix ordering.
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KOVAC Grgur / LLM_value_stability
MIT LicenseUpdated -
parallel-replica / QSD.gen.samples
BSD 3-Clause "New" or "Revised" LicenseC++ software for generating configurations of a molecular system (coordinates and velocities) distributed according to the QSD (Quasi Stationary Distribution) within a user defined metastable state.
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Eye-movement analysis with hidden semi-Markov models to segment phases in reading tasks
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Crash data analysis with hidden Markov random fields with Bayesian Nonparametric priors.
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COMPO / compOC
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Visualize, track and cluster genes based on their expression, intron retention and splicing profile during the Zebrafish development!
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COMPO / HDTwinGen-COMPO
MIT LicenseUpdated -
CHEPIN simulation's code
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Nonlinear mixed-effects modeling and machine learning for oncology
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Valentin Delis / in-situ_simulator
GNU General Public License v3.0 onlyUpdated -
Supplementary datasets and codes for the manuscript "Implication of lipid turnover for the control of energy balance", S. Bernard and K.L. Spalding
This project contains:
a mathematical implementation of the carbohydrate-insulin model (CIM) and an energy-in, energy-out version of the energy-balance model (EBM-IOM) with a component for lipid turnover dynamics.
virtual clinical cohort datasets
numerical simulation results
script files to reproduce numerical simulations
a script file to generate manuscript figures
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Python/R code and Jupyter notebooks accompanying the manuscript, entitled "Single-cell genomics of the mouse olfactory cortex reveals contrasts with neocortex and ancestral signatures of cell type evolution".
See the publication in Nature Neuroscience: https://doi.org/10.1038/s41593-025-01924-3 and its bioRxiv version: https://doi.org/10.1101/2023.08.13.553130
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