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Transparent exploration of machine learning for biomarker discovery from proteomics and omics data.

📰 Open-access article: Transparent exploration of machine learning for biomarker discovery from proteomics and omics data

Citation:
Transparent exploration of machine learning for biomarker discovery from proteomics and omics data
Furkan M Torun, Sebastian Virreira Winter, Sophia Doll, Felix M Riese, Artem Vorobyev, Johannes B Müller-Reif, Philipp E Geyer, Maximilian T Strauss
bioRxiv 2021.03.05.434053; doi: https://doi.org/10.1101/2021.03.05.434053

🟢 OmicLearn.com

More information about Installation & Running is available on our Wiki pages.

• It is strongly recommended to install OmicLearn in its own environment using Anaconda or Miniconda.

  1. Redirect to the folder of choice and clone the repository: git clone https://github.com/OmicEra/OmicLearn
  2. Install the required packages with conda env create --file environment.yml
  3. Activate the environment with conda activate omic_learn

• After a successful installation, type the following command to run OmicLearn:

  streamlit run omic_learn.py --browser.gatherUsageStats False

  Running with Docker option is also available. Please, check the installation instructions on the Wiki pages.

• After starting the streamlit server, the OmicLearn page should be automatically opened in your browser (Default link: http://localhost:8501

The following image displays the main steps of OmicLearn:

Detailed instructions on how to get started with OmicLearn can be found here.

On this page, you can click on the titles listed in the Table of Contents, which contain instructions for each section.

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