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		<identifier>oai:zbc.uz.zgora.pl:79080</identifier>
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<dc:title xml:lang="pl"><![CDATA[Building the library of RNA 3D nucleotide conformations using the clustering approach]]></dc:title>
<dc:creator><![CDATA[Zok, Tomasz]]></dc:creator>
<dc:creator><![CDATA[Antczak, Maciej]]></dc:creator>
<dc:creator><![CDATA[Riedel, Martin]]></dc:creator>
<dc:creator><![CDATA[Nebel, David]]></dc:creator>
<dc:creator><![CDATA[Villmann, Thomas]]></dc:creator>
<dc:creator><![CDATA[Lukasiak, Piotr]]></dc:creator>
<dc:creator><![CDATA[Blazewicz, Jacek]]></dc:creator>
<dc:creator><![CDATA[Szachniuk, Marta]]></dc:creator>
<dc:subject xml:lang="pl"><![CDATA[RNA nucleotides]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[conformer library]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[torsion angles]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[clustering]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[neural gas]]></dc:subject>
<dc:description xml:lang="pl"><![CDATA[An increasing number of known RNA 3D structures contributes to the recognition of various RNA families and identification of their features. These tasks are based on an analysis of RNA conformations conducted at different levels of detail. On the other hand, the knowledge of native nucleotide conformations is crucial for structure prediction and understanding of RNA folding. However, this knowledge is stored in structural databases in a rather distributed form. Therefore, only automated methods for sampling the space of RNA structures can reveal plausible conformational representatives useful for further analysis.]]></dc:description>
<dc:description xml:lang="pl"><![CDATA[Here, we present a machine learning-based approach to inspect the dataset of RNA three-dimensional structures and to create a library of nucleotide conformers. A median neural gas algorithm is applied to cluster nucleotide structures upon their trigonometric description. The clustering procedure is two-stage: (i) backbone- and (ii) ribose-driven. We show the resulting library that contains RNA nucleotide representatives over the entire data, and we evaluate its quality by computing normal distribution measures and average RMSD between data points as well as the prototype within each cluster.]]></dc:description>
<dc:publisher><![CDATA[Zielona Góra: Uniwersytet Zielonogórski]]></dc:publisher>
<dc:contributor><![CDATA[Byrski, Aleksander - ed.]]></dc:contributor>
<dc:contributor><![CDATA[Kisiel-Dorohinicki, Marek - ed.]]></dc:contributor>
<dc:contributor><![CDATA[Dobrowolski, Grzegorz - ed.]]></dc:contributor>
<dc:date><![CDATA[2015]]></dc:date>
<dc:type xml:lang="pl"><![CDATA[artykuł]]></dc:type>
<dc:identifier><![CDATA[http://www.zbc.uz.zgora.pl/repozytorium/Content/79080/AMCS_2015_25_3_18.pdf]]></dc:identifier>
<dc:identifier><![CDATA[https://zbc.uz.zgora.pl/repozytorium/dlibra/publication/88911/edition/79080/content]]></dc:identifier>
<dc:identifier><![CDATA[oai:zbc.uz.zgora.pl:79080]]></dc:identifier>
<dc:source xml:lang="pl"><![CDATA[AMCS, volume 25, number 3 (2015)]]></dc:source>
<dc:source xml:lang="pl"><![CDATA[https://www.amcs.uz.zgora.pl/?action=papers&issue=62]]></dc:source>
<dc:language><![CDATA[eng]]></dc:language>
<dc:relation><![CDATA[oai:zbc.uz.zgora.pl:publication:88911]]></dc:relation>
<dc:rights xml:lang="pl"><![CDATA[Biblioteka Uniwersytetu Zielonogórskiego]]></dc:rights>
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