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davidenoma/README.md
  • 👀 I research Machine Learning, Artificial intelligence, Bioinformatics. This is applied to Genetics & Precision Medicine of Neuropsychiatric disorders, Cancers and Polygenic risk prediction.
  • 👨🏽‍💻 I write Python, R, Java, PHP, Bash, SQL, Javascript associated frameworks and libraries
  • 🚀 I build web, mobile, bioinformatics & data platforms and products.
  • 🌱 I’m currently learning Representation learning and Data engineering pipelines on cloud platforms.
  • 💞️ I want to collaborate and consult on machine learning, data science and bioinformatics projects.
  • 📫 How to reach me [email protected]

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  1. R-Language-scripts R-Language-scripts Public

    Comprehensive collection of scripts and pipelines in R for Bioinformatics & general use. Includes, R fundamentals, bayesian statistics, cancer genomics, data analysis, genomic analysis and targeted…

    R 9

  2. xMLGenoRisk xMLGenoRisk Public

    Machine Learning approach for genetic risk prediction. I applied a modified, XGBoost algorithm and an iterative SNP selection algorithm to find the top features (SNPs) that best predict the risk of…

    Jupyter Notebook 7 2

  3. collaborativebioinformatics/Disease_subsetting collaborativebioinformatics/Disease_subsetting Public

    Colorectal cancer CMs subtyping and personalized medication recommendation based on RNA seq pathway analysis

    Jupyter Notebook 9 2

  4. moka moka Public

    The multi-omics data bridged SNP-set kernel association test (MOKA) Pipeline, implemented using Snakemake for GWAS data by incorporating diverse multi-omics data sources such as gene expression, tr…

    R 1