Artifacts

PhD Dissertation

Probabilistic Machine Learning with Omics Data and Biological Prior Knowledge (PDF)

(Slides from dissertation defense)

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Publications

• David Merrell, Thevaa Chandereng, Yeonhee Park. A Markov Decision Process for Response-Adaptive Randomization in Clinical Trials. Computational Statistics and Data Analysis 2023.
  • Journal article (Feb 2023) (CSDA)
  • preprint manuscript (2021) (arXiv)
  • R package (GitHub)
  • Analysis code (GitHub)
• David Merrell, Anthony Gitter. Inferring Signaling Pathways with Probabilistic Programming. ECCB 2020.
  • preprint manuscript (arXiv)
  • ECCB proceedings (Bioinformatics)
  • codebase (GitHub)
  • ISMB 2020 Talk (YouTube)
  • conference poster (PDF)
• David Merrell, Aws Albarghouthi, Loris D’Antoni. Weighted Model Integration with Orthogonal Transformations. IJCAI 2017.
  • IJCAI 2017 proceedings
  • IJCAI 2017 talk (PDF)
  • conference poster (PDF)

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Other software

• PathwayMultiomics.jl: pathway-regularized matrix factorization for multiomic data

• MatFac.jl: A general-purpose, extensible Julia package for GPU-accelerated matrix factorization (GitHub)

• SparseMatFac.jl: Matrix factorization for data with very few observations

• A pipeline for downloading and storing TCGA data in a useful format (GitHub)
  • or just download the HDF files directly (Zenodo)

• Some Snakemake demos (GitHub)

• Deep learning exercise: attention models for molecules (GitHub)

• Tinkering with the Gen probabilistic programming language (GitHub)

• A Singularity container for deep learning (GitHub)

• ROBDDs in Julia (GitHub)

• Modeling and prediction for sports brackets (GitHub)

• Random idea generator (HTML)

• A Yahtzee solver python package (GitHub) (PyPI)

• A Wordle Julia package (GitHub)

• A Sudoku Julia package (GitHub)

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Other talks

• Preliminary exam (slides)

• Discovery Seminar: A statistical model for multiomic data and biological pathways (slides)

• Managing workflows with Snakemake (slides)

• A Markov Decision Process for block RAR RCT Design (slides)

• Thomson Lab meeting talk (slides)

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Other technical writing

• Preliminary exam written report (PDF)

• Dynamic Bayes Nets and ODEs (PDF)

• Weighted model integration
  • Rotating formulas (PDF)
  • Rational Householder matrices (PDF)
  • The Skitovitch-Darmois theorem (PDF)

• Variational Bayes Inference (PDF)

• Optimization course project
  • Proposal
  • Writeup
  • Code (GAMS)
• Machine learning
  • A fun homework assignment
  • Course project

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Visualizations

• Interactive plots:
  • The Cancer Genome Atlas (TCGA) pathway embedding
  • The Cancer Genome Atlas (TCGA) pathway factors
  • The Cancer Genome Atlas (TCGA) pathway activations
• GIFs:
  • Conway’s game of life
  • Diffusion equation
  • Mandelbrot set zoom
  • N-body Newtonian gravity
  • Approximate Bayesian techniques
    • Variational Inference: outcome space
    • Variational Inference: variational parameter space
    • MCMC sampling
  • Linear regression
    • gradient descent: parameter space
    • gradient descent: fit
    • MCMC: parameter space
    • MCMC: fit