EPIC: An open community challenge for sequence-based prediction of transcription initiation in five non-model metazoans
- 1School of Molecular Biosciences, College of Veterinary Medicine, Washington State University, Pullman, WA, USA
Abstract
Predicting gene expression from DNA sequence is a central problem with critical biological and clinical implications. Recent sequence-to-function models are reported to achieve improved performance, yet it remains unclear how much of what they learn reflects genuine principles of eukaryotic transcription initiation and to what extent they are able to generalize beyond humans and other primary model species. A fair and blind benchmark has likewise been missing. Here we introduce EPIC, the Eukaryotic Promoter and transcription Initiation prediction Challenge. Teams receive strand-specific, single-nucleotide-resolution initiation profiles for 80-95% of the genome and are asked to predict the remainder from DNA sequence alone. To level the field, the challenge relies on understudied animals spanning three phyla: octopus, oyster, milkweed bug, Indian meal moth, and shark. EPIC is open to everyone and closes on December 31, 2026. All teams clearing the dinucleotide precision baseline are invited to join the consortium authorship of the post-challenge publication, and winners are invited for personal authorship.
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BibTeX
@misc{vorontsov2026epic,
title = {{EPIC: An open community challenge for sequence-based prediction of transcription initiation in five non-model metazoans}},
author = {I. E. Vorontsov and N. Gryzunov and B. R. McDonald and V. Kamenets and T. Salimgareev and I. Kozin and The EPIC Consortium and A. M. Conard and D. Penzar and I. Grosse and V. J. Makeev and P. Bucher and I. V. Kulakovskiy and S. H. Duttke},
howpublished = {bioRxiv},
year = {2026},
month = sep,
doi = {10.64898/2026.09.16.752171},
url = {https://www.biorxiv.org/content/10.64898/2026.09.16.752171v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - EPIC: An open community challenge for sequence-based prediction of transcription initiation in five non-model metazoans
AU - I. E. Vorontsov
AU - N. Gryzunov
AU - B. R. McDonald
AU - V. Kamenets
AU - T. Salimgareev
AU - I. Kozin
AU - The EPIC Consortium
AU - A. M. Conard
AU - D. Penzar
AU - I. Grosse
AU - V. J. Makeev
AU - P. Bucher
AU - I. V. Kulakovskiy
AU - S. H. Duttke
PY - 2026
DA - 2026/09/16
PB - bioRxiv
DO - 10.64898/2026.09.16.752171
UR - https://www.biorxiv.org/content/10.64898/2026.09.16.752171v1
AB - Predicting gene expression from DNA sequence is a central problem with critical biological and clinical implications. Recent sequence-to-function models are reported to achieve improved performance, yet it remains unclear how much of what they learn reflects genuine principles of eukaryotic transcription initiation and to what extent they are able to generalize beyond humans and other primary model species. A fair and blind benchmark has likewise been missing. Here we introduce EPIC, the Eukaryotic Promoter and transcription Initiation prediction Challenge. Teams receive strand-specific, single-nucleotide-resolution initiation profiles for 80-95% of the genome and are asked to predict the remainder from DNA sequence alone. To level the field, the challenge relies on understudied animals spanning three phyla: octopus, oyster, milkweed bug, Indian meal moth, and shark. EPIC is open to everyone and closes on December 31, 2026. All teams clearing the dinucleotide precision baseline are invited to join the consortium authorship of the post-challenge publication, and winners are invited for personal authorship.
ER -