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Project files provided as supporting information to the manuscript "An information theory-based approach for optimal model reduction of biomolecules"

Marco Giulini; Roberto Menichetti; Raffaello Potestio


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        <foaf:name>Roberto Menichetti</foaf:name>
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        <foaf:name>Raffaello Potestio</foaf:name>
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    <dct:title>Project files provided as supporting information to the manuscript "An information theory-based approach for optimal model reduction of biomolecules"</dct:title>
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    <dct:description>&lt;p&gt;The dataset contains the following files:&lt;/p&gt; &lt;ul&gt; &lt;li&gt;- adenylate.zip&lt;/li&gt; &lt;li&gt;- antitrypsin.zip&lt;/li&gt; &lt;li&gt;- tamapin.zip&lt;/li&gt; &lt;li&gt;- analysis_notebooks.zip&lt;/li&gt; &lt;/ul&gt; &lt;p&gt;Each of these refers to one of three proteins. For each CG sites number N, each compressed folder contains the following files:&lt;/p&gt; &lt;ul&gt; &lt;li&gt;random mappings (random_mappings_${N}.txt)&amp;nbsp;&lt;/li&gt; &lt;li&gt;random mapping entropies (random_smaps_${N}.txt) [fig1]&lt;/li&gt; &lt;li&gt;optimal mappings (lowest_mappings_${N}.txt) [fig3, fig4, figS2]&lt;/li&gt; &lt;li&gt;optimal mapping entropies (lowest_smaps_${N}.txt) [fig1]&lt;/li&gt; &lt;li&gt;pdb files with conservations probabilities in the beta factor column (${N}_probs.pdb) [fig4, figs2]&lt;/li&gt; &lt;li&gt;SASA values (${protein_name}_SASA_residues.xvg&amp;nbsp;&lt;/li&gt; &lt;li&gt;transition mapping entropies (${protein_name}_transition_smaps.txt) [fig2]&lt;/li&gt; &lt;li&gt;additional transition mapping entropies (${protein_name}_transition_smaps*) [figs3]&lt;/li&gt; &lt;/ul&gt; &lt;p&gt;The file&amp;nbsp;analysis_notebooks.zip contains the python3 notebooks employed to perform all the analysis present in the paper:&lt;/p&gt; &lt;ul&gt; &lt;li&gt;paper_analysis_adenylate.ipynb&lt;/li&gt; &lt;li&gt;paper_analysis_antitrypsin.ipynb&lt;/li&gt; &lt;li&gt;paper_analysis_tamapin.ipynb&lt;/li&gt; &lt;/ul&gt; &lt;p&gt;Packages required for the usage of these python 3 scripts:&lt;/p&gt; &lt;p&gt;- numpy&lt;br&gt; - pandas&lt;br&gt; - matplotlib&lt;br&gt; - seaborn&lt;br&gt; &amp;nbsp;&lt;/p&gt;</dct:description>
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