From January 22-24, 2018, the NCBI will help with a data science hackathon on the NIH campus in Bethesda, MD. The hackathon will focus on general data science analyses, including text, image and sequence processing. This event is for researchers, including students and postdocs, who have already engaged in the use of large datasets or in the development of pipelines for analyses from high-throughput experiments. Some projects are available to other non-scientific developers, mathematicians, or librarians.
The event is open to anyone selected for the hackathon and willing to travel to the NIH campus (see below). Applications are due Friday, December 22nd, 2017 by 9 pm EST.
Working groups of five to six individuals will be formed into five to eight teams. These teams will build pipelines and tools to analyze large datasets within a cloud infrastructure. Potential subjects for this iteration include:
- A machine learning tool for observing structural changes in time course light microscopy
- Automated systematic review methodology
- Splitting BLAST databases on the cloud
- A data mapping tool to assist users with mapping their data to CDEs
- Disease clustering from literature based on limited training data (phenotypic information)
- Variants from RNA-Seq (including single cell)
- Graphical User Interface for gene expression calculated on the fly from raw data
- Analysis of agricultural calorimetry experiments
Please see the application form for more details and additional projects. The project list will continue to evolve and will be updated on the application form.
After a brief organizational session, teams will spend three days addressing a challenging set of scientific problems related to a group of datasets. Participants will analyze and combine datasets to work on these problems.
Datasets will come from public repositories or will be supplied by the project lead. During the hackathon, participants will have an opportunity to include other datasets and tools for analysis. Please note, if you use your own data during the hackathon, we ask that you submit it to a public database within six months of the end of the event.
All pipelines and other scripts, software and programs generated in this hackathon will be added to a public GitHub repository. Manuscripts describing the design and usage of the software tools constructed by each team may be submitted to an appropriate journal such as the F1000Research hackathons channel.
To apply, complete this form (approximately 10 minutes to complete). Applications are due Friday, December 22nd, 2017 by 9 pm PT. Participants will be selected based on the experience and motivation they provide on the form. Prior participants and applicants are especially encouraged to apply. The first round of accepted applicants will be notified on December 25th by 10 pm ET, and have until January 2nd at noon ET to confirm their participation. If you confirm, please make sure it is highly likely you can attend, as confirming and not attending prevents other data scientists from attending this event. Please include a monitored email address, in case there are follow-up questions.
Note: Participants will need to bring their own laptop to this program. A working knowledge of scripting (e.g., Shell, Python, R) is necessary to be successful in this event. Employment of higher level scripting or programming languages may also be useful. Applicants must be willing to commit to all three days of the event.
No financial support for travel, lodging or meals is available for this event.
Also note that the hackathon may extend into the evening hours on Monday and/or Tuesday. Please make any necessary arrangements to accommodate this possibility.
Please contact email@example.com with any questions.
Venue: NIH campus
Additional Projects: If you have an additional project you would like to see added to the form, please submit it here.