Deadline approaching for entry into EMGS Bioinformatics Challenge 2020

Attention data scientists and genetic and computational toxicologists!

Applications are being accepted for the EMGS Bioinformatics Challenge 2020, to be held at the annual EMGS meeting from September 12 to 16, 2020, in Palm Springs, Calif.

The goal of the competition is to generate interaction between EMGS members and bioinformatics/data science experts. Members are encouraged to work together to develop novel tools and approaches that harness publicly available “big data” to identify signatures of genotoxic hazards and provide insight into their mechanisms of action.

Please submit a 250-word abstract with a data visualization and/or any inquiry to by April 15. You will receive a confirmation email upon submission. Selected participants will receive (a) a $300 monetary award for academic participants and (b) a membership waiver for non-member participants. The abstracts will be evaluated by four criteria:

(1) Model performance in classifying/predicting carcinogens

(2) Identification of a novel genotoxic mode(s) of action

(3) Effectiveness of the data visualization

(4) Originality and innovation

Participating groups will then be invited to send representatives to present their work at the EMGS 2020 annual meeting and compete for the grand prize of $1,200.

We welcome any data-intensive study that involves genomics, proteomics, metabolomics, and high-throughput data, including (but not limited to):

(1) Tox21/ToxCast

(2) Drug Matrix

(3) TG-Gates

(4) Health Canada

(5) Toxicogenomics Dataset

(6) Litron Labs MultiFlow® DNA DamageDataset

(7) NCI-60 Human Tumor Cell line Screen

Please see for further information and updates. Let us bring DNA and data science together!


Attention EMGS Members: We know there is uncertainty with the situation surrounding COVID-19 and if there is a need to postpone or cancel the meeting there will be complete refunds for registration. Contingency plans are being worked on for a hybrid meeting. Click here to learn more.

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