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Python Hackathon

Many of you who enjoyed the Collaboratory workshops have requested the opportunity to continue improving your computational skills beyond the workshop. We're pleased to announce a new event for those with interest in computational and quantitative methods in biology: a Hackathon dedicated to solving problems of interest to our community, using Python.

Table of contents

Our idea is to organize a Hackathon over a single day (December 8th, 2017), and spend this day solving a set of coding problems. These coding problems will consist of common issues faced by many of us in our research. Collaboratory fellows will be present throughout the whole day to provide personal and tailored assistance. We will encourage every participant to go in their own pace and speed. Collaborative work in groups is also encouraged.

To ensure that these problems are of relevance to a large number of people, we are asking for everyone interested to submit suggestions of problems that you, or colleagues, may want help tackling. This is a great opportunity to get help with a problem you're stuck on as we learn together how to overcome coding challenges. With a set of relevant problems, we can offer tailored assistance in advanced topics with Python, creating a stronger connection between the contents of our workshop and your research and going beyond the basic material provided by the current Collaboratory workshop. The hackathon is suitable for anyone who regularly uses or wishes to regularly use Python for their research, regardless of their level of expertise with programming languages. The only requirement is the Introduction to Python workshop.

  • This Hackathon will be hosted by the QCBio Collaboratory.

  • Official home page of the Hackathon.

  • Slides presented at the beggining of the Hackathon.

  • For more information or to contact us, please send us an e-mail: thmosqueiro@ucla.edu

  • Want to make comments that are visible to everyone in the Hackathon? We can use our Issues page to share general comments and questions relevant to everyone. You'll need an account (takes 2 minutes to create one!), but no knowledge of git is required.

When? Where?

  • Date: December 8th, 2017
  • Where: Collaboratory Classroom (Boyer Hall 529), Institute for Quantitative and Computational Biology, UCLA
  • What time: between 9:00AM and 5:00PM
  • Lunch will be served between 12:30 and 2PM

Registration and contact

To register, follow this link: https://goo.gl/forms/oAVIl67OUEBMkHaR2

To ensure that the problems used in the Hackathon are of relevance to a large number of people, during the registration we ask for suggestions of problems that you, or colleagues, may want help tackling. These suggestions can be anything, and you don't need to submit a solution, just a small description of the problem. Examples of types of problems: changing file format from one standard to another; automating a task or pipeline for many datasets; optimize the computation time of complex analyses and pipelines; applying basic methods of computer vision to segment images (e.g. for cell detection); building predictive models (e.g. using Machine Learning techniques); solving a model of ODEs to fit your data; etc.

Schedule

Here is a tentative schedule:

Time Event
9:00 - 9:30 Initial set ups and chat
9:30 - 10:00 Quick presentation about the Hackahton and overview of the problems
10:00 - 12:30 First coding session
12:30 - 2:00pm Lunch while coding
2:00 - 4:00 Second coding session
4:00 - 4:30 Final remarks and discussions about the future
4:30 - 5:00 Summary of what was done in each project

Coding problems

During the Hackathon, we will be solving together the following problems. You should feel free to participate in as many problems you want. The list of problems may be updated until the date of the event.

  1. Analysis of calcium imaging. We will use videos of fluorescent calcium indicator Oregon Green in endothelial cells to practice how to extract fluorescence time series of a set of cells and estimate their calcium concentration.

  2. Simulating protein expression with the Gillespie method. To explore this method, we will create a model that predicts expression levels of the Hok-Sok system, a postsegregational killing mechanism often used as kill switch in synthetic biology.

  3. Automating a pipeline for image processing. Using a single-molecule Fluorescence-in-Situ-Hybridization dataset, we will explore how to automate a simple pipeline for image processing in Python using parallel techniques.

  4. Automated submission of analyses to online servers. Let's construct a Python script that automatically submits fasta files to the SignalP 4.1 Server, which predicts the presence and location of signal peptide cleavage sites in aminoacid sequences. Scripts that are able to navigate through web pages are called "web crawlers" and are very useful for many applications!

  5. Recording fluorescence using camera and arduino. Let's design and set up a small system to simultaneously control an LED array and a camera to record a fluorescence tracer such as fluorescein.

Who is this Hackathon intended for?

The hackathon is suitable for anyone who regularly uses or wishes to regularly use Python for their research, regardless of their level of expertise with programming. The only requirement is the Introduction to Python workshop. Read more about this in our Frequently asked questions.

Organization

This event is sponsored by the QCBio Collaboratory, and was organized by the following fellows:

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