Data for "Generative and interpretable machine learning for aptamer design and analysis of in vitro sequence selection"

<p>Once decompressed, the file contains a folder which contains:</p> <ul> <li>The files &quot;s100_Nth.fasta&quot; (where &quot;N&quot; is 5, 6, 7 or 8), which are the output of the SELEX experiment described in the paper with DOI:&nbsp;<a href="https://doi.org/10.1002/cbic.201900265">10.1002/cbic.201900265</a>. They are standard fasta files, and the descriptor of each sequence is of the form &quot;seqX-Y&quot;, where &quot;X&quot;&nbsp;is an increasing label, and &quot;Y&quot; is the number of times &quot;seqX&quot;&nbsp;has been obtained (number of counts of &quot;seqX&quot;).</li> <li>The file &quot;Aptamer_Exp_Results.csv&quot;, which contains the sequences tested experimentally for the paper &quot;Generative and interpretable machine learning for aptamer design and analysis of in vitro sequence selection&quot; (preprint available at https://doi.org/10.1101/2022.03.12.484094), with the following experimental results for each sequence: (i) whether the sequence was able to bind thrombin (&#39;B&#39; for binders, &#39;NB&#39; for non-binders); (ii) the thrombin exosite used for binding&nbsp;(&#39;I&#39; for exosite I, &#39;II&#39;&nbsp;for exosite II, &#39;n/a&#39; for sequences not tested).</li> </ul> <p>Examples of usage of the data are available at&nbsp;https://github.com/adigioacchino/RBMsForAptamers.</p>