(9/13) Post-challenge analysis added extra DL models: top models from the DREAM challenge and popular architectures unused in IBIS, including Malinois and DNA language models. Fine-tuned DNA LMs performed far worse than fully supervised approaches.

(8/13) TF-binding models can be used to predict the effect of single-nucleotide variants. In A2G, PWMs performed unexpectedly well, e.g. MEX secured 2nd place. In G2A, the original top triple-A models dominated, followed by MEX and RSAT — the strongest PWM-based approach.

(5/13) Once again, we congratulate the runner-up teams (Medici, Salimov & Frolov lab, callitmagic), and the winners (Bench Pressers, mj, and Biology Impostor) (x.com/halfacrocodi...)

(3/13) For the first time, the IBIS Challenge assessed in depth the transferability of DNA motif models from artificial to genomic sequences (A2G), and vice versa (G2A), with rigorous test-train splits, multiple performance metrics, and transparent ranking system.

(1/13) Excited to share the outcome of the IBIS Challenge! The IBIS challenge united dozens of teams across the world in tackling the problem of modeling transcription factor (TF) binding specificity using a diverse collection of experimental datasets for understudied human TFs.

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