🐦 The IBIS Challenge

<p>

Join <strong>the IBIS Challenge</strong>: an open competition in <strong>I</strong>nferring and predicting transcription factor <strong>Bi</strong>nding <strong>S</strong>pecificities.</p>
<p>Deciphering human gene regulation is a cornerstone of <em>modern molecular biology and biomedicine</em>. On the regulatory sequence level, the grammar of the gene regulation is defined by the binding specificities of special proteins, <em>the transcription factors</em>, which act at particular "genomic addresses" by recognizing 🧬 DNA sequence patterns in gene regulatory regions. Drawing inspiration from <em>DREAM and Kaggle competitions</em>, <strong>we invite you to join IBIS</strong> (<a href="https://ibis.autosome.org/" rel="nofollow">ibis.autosome.org</a>), an open challenge in computational sequence analysis for Inferring Binding Specificities of human transcription factors with classic bioinformatics and advanced machine learning (ML).</p>
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<p>IBIS aims at a fair assessment of <strong>existing and novel methods solving the long-standing problem of DNA motif discovery: identifying and modeling recurrent DNA text patterns</strong> recognized by human transcription factors. In IBIS, we will assess classic methods as well as diverse modern approaches of arbitrary complexity. </p>
<p>🚀 Those include but are not limited to <strong>decision trees</strong> on top of k-mer frequencies, hidden markov models (<strong>HMMs</strong>), convolutional neural networks (<strong>CNNs</strong>), recurrent neural networks (<strong>RNNs</strong>), long short-term memory (<strong>LSTM</strong>) models, as well as <strong>attention</strong> and <strong>transformer-based models</strong>.</p>
<p>💡 <strong>IBIS allows arbitrary usage of the human genome or random DNA sequences to pre-train</strong> an artificial neural network <strong>or to extract features</strong> if performed from scratch. Particularly we allow using:</p>
<ul>
<li><strong>hg38 human genome</strong> assembly (including any existing <em>DNA language models pretrained solely on the genome sequence</em>);</li>
<li>precomputed biophysical features derived from the DNA sequences, such as the <strong>DNA shape features</strong>;</li>
<li>RepeatMasker track;</li>
<li><strong>protein-level metadata on transcription factors</strong> (including but not limited to protein sequence and domain information) available directly in UniProt (so, in theory, you can demonstrate <em>the power of pre-training on protein sequences</em>).
More details can be found in the <a href="https://ibis.autosome.org/docs/technical_details" rel="nofollow">IBIS documentation</a>.</li>
</ul>
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<p>📊 To solve the challenge problem, IBIS provides a <strong>diverse array of unpublished experimental data on 40 human regulatory proteins</strong>, many of which remain unexplored in terms of preferred DNA binding patterns. </p>
<p>The challenge proceeds in two stages: <em>the online Leaderboard</em> (10 transcription factors) and <em>the offline Final</em> round (the remaining 30 transcription factors). Winners will be announced separately for each of the stages. <strong>🏆 The best methods of both stages 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.</strong></p>
<ul>
<li>Learn more at <a href="https://ibis.autosome.org/" rel="nofollow">the IBIS Challenge website</a></li>
<li>Read <a href="https://twitter.com/halfacrocodile/status/1767284083632095646" rel="nofollow">The IBIS Challenge Twitter Thread</a></li>
<li>Organizers: <a href="https://ibis.autosome.org/docs/about_us" rel="nofollow">GRECO-BIT &amp; Codebook consortia</a></li>
</ul>
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