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  1. a framework for training sequence-level deep learning networks

    Jupyter Notebook 303 79

  2. Documentation and scripts to run HeartENN (Richter et al., 2020)

    Python 1 2

  3. Methods to build a network of pathway co-occurrence relationships out of expression signatures extracted from transcriptomic compendia.

    Python 4 3

  4. This repository is in support of the PathCORE-T paper (https://doi.org/10.1101/147645). It contains all the code and necessary data/metadata to repeat all analyses in the paper.

    Jupyter Notebook 7 2

  5. Python implementation of Donato et al. (2013)'s maximum impact estimation. A pre-processing step to pathway analysis.

    Python 1

131 contributions in the last year

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Contribution activity

May 2022

13 contributions in private repositories May 5 – May 6

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