Post
1911
🐦 The IBIS Challenge: an open competition in Inferring and predicting transcription factor Binding Specificities: modeling DNA patterns recognized by human regulatory proteins.
🧬 Deciphering human gene regulation is a cornerstone of modern molecular biology and biomedicine. Gene activity is controlled by special regulatory proteins, the transcription factors, which recognize DNA sequence patterns. We invite you to join IBIS in our search for the best method to model binding specificities of yet unexplored human regulatory proteins.
In the challenge, you may use classic methods to represent sequence patterns or any modern approaches
🚀 including decision trees, CNNs, RNNs, LSTMs, and transformers.
💡IBIS allows using arbitrary genome or random sequences to pre-train an artificial neural network or to extract features, and use a few existing datasets, see the IBIS documentation (https://ibis.autosome.org/docs/technical_details).
📊 Yet, the main power and opportunity come with a diverse array of experimental data on 40 human regulatory proteins, many of which remained unexplored until now.
🏆 The best methods will be highlighted in the post-challenge high-impact scientific paper 📝, while the winners 🥇of the Primary track of the Final round will be invited to contribute as co-authors.
🌐 Learn more at https://ibis.autosome.org/
🤗 Our article at HF: https://huggingface.co./blog/nikgr/the-ibis-challenge
👥 Organizers - GRECO-BIT & Codebook consortia: https://ibis.autosome.org/docs/about_us
🧬 Deciphering human gene regulation is a cornerstone of modern molecular biology and biomedicine. Gene activity is controlled by special regulatory proteins, the transcription factors, which recognize DNA sequence patterns. We invite you to join IBIS in our search for the best method to model binding specificities of yet unexplored human regulatory proteins.
In the challenge, you may use classic methods to represent sequence patterns or any modern approaches
🚀 including decision trees, CNNs, RNNs, LSTMs, and transformers.
💡IBIS allows using arbitrary genome or random sequences to pre-train an artificial neural network or to extract features, and use a few existing datasets, see the IBIS documentation (https://ibis.autosome.org/docs/technical_details).
📊 Yet, the main power and opportunity come with a diverse array of experimental data on 40 human regulatory proteins, many of which remained unexplored until now.
🏆 The best methods will be highlighted in the post-challenge high-impact scientific paper 📝, while the winners 🥇of the Primary track of the Final round will be invited to contribute as co-authors.
🌐 Learn more at https://ibis.autosome.org/
🤗 Our article at HF: https://huggingface.co./blog/nikgr/the-ibis-challenge
👥 Organizers - GRECO-BIT & Codebook consortia: https://ibis.autosome.org/docs/about_us