November 3-4, 2026 · Cold Spring Harbor Laboratory, New York · In person
Register for BioDATA ASCENT
Join the BioDATA ASCENT code-a-thon, an intensive, hands-on event where early-career researchers use cloud computing, AI, and large-scale biological and biomedical data to turn interesting biological questions into working analyses.
Hosted by Allissa Dillman (BioDataSage) and Michael Schatz (JHU) immediately before the 2026 CSHL Biological Data Science Conference, this collaborative code-a-thon is designed especially for PhD students and postdocs. You’ll work in small teams alongside peers and mentors to explore real NIH-supported datasets, learn practical computational skills, and build something tangible: a prototype, analysis, reusable workflow, visualization, or next-step plan for a research project.
Brought to you by the Common Fund Data Ecosystem (CFDE) and the NHGRI AnVIL programs, ASCENT brings together AI, Science, Cloud, Exploration, Networks, and Technology. No fully formed project is required: bring a scientific question, a technical skill, an early idea, or simply curiosity and a willingness to collaborate.
What you’ll explore
Teams will have access to large biomedical datasets and resources from NIH Common Fund Data Ecosystem and the NHGRI AnVIL, including:
- GTEx gene-expression data across human tissues
- HuBMAP molecular and spatial maps of human cells
- Kids First pediatric genomic data
- MoTrPAC multimodal data on molecular responses to physical activity
- T2T references and HPRC Pangenomes
- 1000 Genomes DNAseq and MAGE RNAseq resources
- NIH Intramural Center for Alzheimer’s and Related Dementias (CARD) Long reads
- Cloud computing resources from the CFDE Cloud Workspace Implementation Center (CWIC) and NHGRI AnVIL
- Many additional NIH-supported datasets and cloud-based research resources
What you might build
Projects can take many forms. Teams can:
- Use machine learning or AI to predict tissue type, disease state, drug response, or other characteristics from multi-omics data
- Predict drug efficacy and side effects across populations
- Investigate the molecular impacts of exercise on health and diseases
- Leverage the human pangenome to improve the analysis of human genetic diversity
- Develop new approaches for finding, combining, and interpreting biomedical data
- Test AI-assisted methods for research discovery
- Turn a promising research question into an initial analysis or prototype
Have an idea for a potential team project? Please reach out to Allissa Dillman and Mike Schatz to discuss it further.
By the end of the event, each team will present what they built, draft blog posts & manuscripts, identify next steps, and make connections that can continue beyond the code-a-thon.
Schedule
Tuesday, November 3 @ 7:00 - 9:00 pm ET
Welcome, orientation, and team formation
- Meet fellow participants and mentors
- Get an overview of available datasets, cloud resources, and project possibilities
- Share ideas, pitch projects, and form teams
Wednesday, November 4 @ 9:00 am - 5:00 pm ET
Project Day
- Morning: Team-based project development
- Midday: Progress check-ins, mentor support, and cross-team discussion
- Afternoon: Final development, documentation, and preparation of results
- By 5:00 p.m.: Team presentations, wrap-up, and next steps
- Dinner begins at 5:30, the main conference opens at 7:30pm
Dinner will be available from 5:30-7:00 p.m. on both days. Breakfast is served from 7:30-9:00 a.m., and lunch from noon-1:30 p.m.
What to bring
Bring your laptop, your ideas, and your curiosity. You are welcome to arrive with a research question, project concept, or technical skill to share, but none are required.
Registration
Participants with a range of biological and computational backgrounds are welcome; no prior cloud-computing or AI experience is required.
Register for the BioDATA ASCENT code-a-thon using our participant registration form. There is no cost to join the code-a-thon.
The additional night of housing on November 3 costs $255. This charge includes dinner on November 3 and meals on November 4. Participants attending the Biological Data Science Conference should make sure to request housing beginning November 3.
Questions?
Keep an eye on the BioDATA-ASCENT GitHub or email mschatz@cs.jhu.edu and adillman@biodatasage.com
Acknowledgements
Thanks to the NIH Common Fund Data Ecosystem (CFDE) Training Center, CFDE Cloud Workspace Implementation Center (CWIC), NHGRI AnVIL, and Cold Spring Harbor Laboratory