Submissions now being accepted for EMGS Bioinformatics Challenge 2021

Attention computer scientists, bioinformaticians, data scientists, genome scientists, and environmental toxicologists! We are now accepting submissions for the EMGS Bioinformatics Challenge 2021. We are currently seeking abstracts in any one of the following three areas:

(1) Novel computational approaches including machine learning and artificial intelligence (AI) on high-throughput, high-content, exposure-risk assessment, and/or clinical data classification.

(2) Genetic/genomic toxicological applications of model organism databases, including EcoCyc E. coli database, Saccharomyces genome database, WormBase, wFleaBase, Xenbase, and ZFIN.

(3) Predictive modeling with genomic/mutation/epimutation datasets, and/or toxicology databases, including Tox21/ToxCast, Drug Matrix, TG-Gates, Comparative Toxicogenomics Database, and SeqAPASS.

Please submit a 250-word abstract with a data visualization or conceptual workflow pipeline to by February 28th, 2021. You will receive a confirmation email upon submission. The abstracts will be evaluated by four criteria:

  • Model performance in classifying/predicting carcinogens; and/or identification of a novel genotoxic mode(s) of action (50%)
  • Effectiveness of the data visualization (25%)
  • Originality and innovation (25%)

Selected participants will receive a $100 monetary award and present their work in the preliminary round of the competition. It will be held as a virtual symposium in Spring 2021. The finalist teams will be invited to present during the 2021 EMGS Virtual Annual Meeting, and compete for the grand prize of $1000. Please submit any inquiry to The past winners of the 2020 competition can be found here:

Maxwell Leung, Ph.D. (Arizona State University, Co-chair)

Jeffrey Bemis, Ph.D. (Litron Laboratories, Co-chair)

Kathleen Hill, Ph.D. (Western University)

Thomas Wilson, M.D., Ph.D. (University of Michigan)

Tess Leuthner (Duke University)

Organizing Committee, 2021 EMGS Bioinformatics Challenge

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