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Toronto Bioinformatics Hackathon

README.md

Welcome to Toronto Bioinformatics Hackathon!

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🎯 September 19 – 21, 2025

The Toronto Bioinformatics Hackathon is a student-led computational biology hackathon that brings together early career bioinformaticians, molecular biologists, statisticians, and computer scientists from Toronto’s Discovery District to complete interdisciplinary projects that emphasize computational and entrepreneurial thinking.

In partnership with Deep Genomics, the Terrence Donnelly Centre and the Temerty Faculty of Medicine's Computational Biology in Molecular Genetics program, participants will collaborate to develop innovative solutions to key challenges in computational biology, with commercialization potential.

✨ Looking Ahead to 2025

We’re excited to welcome a new cohort of participants to the 2025 Toronto Bioinformatics Hackathon! Stay tuned for updates as we prepare another weekend of collaboration, innovation, and discovery in computational biology.

Our Deepest Gratitude to Our Sponsors

        

        

                 

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  1. rna-expression-from-sequence rna-expression-from-sequence Public

    🥇 Winner of the First Place award: Design a model to predict protein binding affinity to specific DNA sequences using known transcription factors and their binding sites.

    Python 1 1

  2. cite-seq-foundation-model-evaluation cite-seq-foundation-model-evaluation Public

    🥈 Winner of the Runner Up award: Evaluating foundation models for predicting surface protein abundance from RNA expression.

    Jupyter Notebook 1

  3. disease-susceptibility-analysis disease-susceptibility-analysis Public

    🏆 Winner of the Perseverance award: Create a tool capable of predicting susceptibility to disease in remote or otherwise underserved areas.

    HTML 2

  4. diffusion-deconvolution-dia-msms diffusion-deconvolution-dia-msms Public

    Forked from Roestlab/diffusion-deconvolution-dia-msms-data

    🚀 Winner of the Donnelly Centre Innovation and Commercialization award: Apply diffusion models to deconvolute highly multiplexed DIA-MS/MS data by conditioning on MS1 signals to generate cleaner MS…

    Jupyter Notebook 1

  5. website website Public

    Toronto Bioinformatics Hackathon Website

    HTML

  6. .github .github Public

    Toronto Bioinformatics Hackathon GitHub README

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