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RemyLau/README.md

Hi there πŸ‘‹

I am a Postdoctoral Fellow in the Ray and Stephanie Lane Computational Biology Department at Carnegie Mellon University. I currently work on developing computational and machine learning methods, as well as software, for analyzing and understanding single-cell epigenomics.

I obtained my Ph.D. degree in the Department of Computational Mathematics, Science & Engineering (CMSE) at Michigan State University. My training focused on network biology, graph representation learning, spectral graph theory, and machine learning.

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πŸ›  I’m currently developing

  • Stay tuned! Something exciting is going online soon!

🧰 I'm actively maintaining several packages related to my past / recent projects

  • obnb [paper]: a Python toolkit for setting up benchmarking datasets using publicly available biomedical networks and gene annotation resources. A comprehensive benchmarking study with various graph neural networks and graph embedding methods is presented in obnbench.
  • DANCE [paper]: an extensive toolkit for deep learning with single-cell (multi-)omics data.
  • PecanPy [paper]: a memory efficient and Numba accelerated Python implementation of node2vec with an improved version node2vec+ [paper] for weighted graphs.
  • PyGenePlexus [paper]: a network-based gene classification service using machine learning and gene interaction network features.
  • GTaxoGym [paper]: a taxonomic study of benchmarking graph datasets from various domains based on the GNN model sensitivity to a collection of graph perturbations.

πŸ“« Find out more about my work and reach out to me

⚑ Side projects

  • ✍️ I share my passion about network biology and machine learning via blog posts on Medium
  • πŸ‘€ I create mathematical and algorithmic visualizations using Manim, which was first developed and used by my favorite math YouTube channel 3Blue1Brown.
  • πŸ€— I contribute to open source projects in various ways
  • πŸ“¦ I work on several small packages on the side to help improve my production workflow and exercise my dev workflow
    • pydab: a tool for working with dab files used by Sleipnir, a C++ library for machine learning on genomic data.
    • py2zenodo: a command line tool for uploading data to Zenodo
    • fastauroc: a Numba accelerated computation of the area under the receiver operating characteristic.

Installation notes

conda create -n remylau python=3.11 -y && conda activate remylau

pip install -e .

conda clean --all -y

Pinned Loading

  1. G-Taxonomy-Workgroup/GPSE G-Taxonomy-Workgroup/GPSE Public

    Graph Positional and Structural Encoder

    Python 42 3

  2. krishnanlab/obnb krishnanlab/obnb Public

    A Python toolkit for setting up benchmarking dataset using biomedical networks

    Python 21 1

  3. krishnanlab/PecanPy krishnanlab/PecanPy Public

    A fast, parallelized, memory efficient, and cache-optimized Python implementation of node2vec

    Python 157 22

  4. OmicsML/dance OmicsML/dance Public

    DANCE: a deep learning library and benchmark platform for single-cell analysis

    Python 352 36

  5. G-Taxonomy-Workgroup/GTaxoGym G-Taxonomy-Workgroup/GTaxoGym Public

    Taxonomy of Benchmarks in Graph Representation Learning

    Python 19

  6. krishnanlab/PyGenePlexus krishnanlab/PyGenePlexus Public

    A network based gene classification library to generate genome wide predictions about genes that are functionally similar to the input gene list.

    Python 20 3