Copenhagen Bioinformatics Hackathon 2020 - Hack-from-home Edition

Copenhagen Bioinformatics Meetup
Copenhagen Bioinformatics Meetup
Public group

Online event

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The Copenhagen Bioinformatics Hackathon 2020 will be a hack-from-home weekend of bioinformatics, data science, coding, and fun. The event will gather students, researchers, and entrepreneurs with backgrounds in bioinformatics, computer science, data science, software development, computational biology, and related fields. In small teams, you will have 40 hours to come up with ideas and develop an innovative solution to one of the challenges. The challenges include using machine learning to identify fake academic papers, modelling proteins and interactions, predicting pathogenicity, generating visual art based on nucleotide sequences, and many more. The hackathon is put on by Computational BioVikings and BioLib. Will you join us in shaping the future of biomedical research in Denmark?

If you are in doubt whether you can set aside a whole weekend to attend the hackathon here are three good reasons you can use to convince yourself:
- First, it will be a lot of fun!
- Second, you get to meet, and work with top talented bioinformaticians and data scientists.
- Third, the event will be a chance for you to start new projects and collaborations with other participants or mentors.

🧬Sneak peak of the CHALLENGES:
- Art from your DNA
- Fake Paper Detector
- Protein Origami: 3D folding with deep learning
- Crawling the Web for MD Simulations
- Better diagnostics for Lynch Syndrome
- Mutation Pathogenicity Prediction
- Better diagnostics for Heart Disease
- Find genetic associations for fat content in pancreas and liver tissues
-Integrative clusters predictor for breast cancer

📍Location: From home
👥Teams are from 2 to 5 people. If you don't have a team yet, do not worry, we will help you match up with some awesome people.

✏️Registration closed

📰 More information will follow soon, stay tuned!

📩 If you have any questions or ideas regarding the hackathon send a message to us on [masked].