bioRxivBioinformaticsPreprint
EPIC: An open community challenge for sequence-based prediction of transcription initiation in five non-model metazoans
Ilya E. VorontsoviD, Nikita GryzunoviD, Bayley R. McDonaldiD, Vasily Kamenets, Timur Salimgareev, Ivan KoziniD, Ashley Mae ConardiD, Dmitry PenzariD, Ivo GroßeiD, Vsevolod J. MakeeviD, Philipp BücheriD, Ivan V. KulakovskiyiD, Sen LiuiD
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.
- organism: non-human primate
- organism: mouse
- organism: rat
- assay: whole-genome sequencing
- research focus: benchmarking
- approach: statistical model
- approach: machine learning (classical)
- Citations
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