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      <subfield code="a">Lang, Benjamin</subfield>
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      <subfield code="a">Armaos, Alexandros, 1989-</subfield>
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      <subfield code="a">Tartaglia, Gian Gaetano</subfield>
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      <subfield code="a">Protein-RNA interactions are implicated in a number of physiological roles as well as diseases, with molecular mechanisms ranging from defects in RNA splicing, localization and translation to the formation of aggregates. Currently, ∼1400 human proteins have experimental evidence of RNA-binding activity. However, only ∼250 of these proteins currently have experimental data on their target RNAs from various sequencing-based methods such as eCLIP. To bridge this gap, we used an established, computationally expensive protein-RNA interaction prediction method, catRAPID, to populate a large database, RNAct. RNAct allows easy lookup of known and predicted interactions and enables global views of the human, mouse and yeast protein-RNA interactomes, expanding them in a genome-wide manner far beyond experimental data (http://rnact.crg.eu).</subfield>
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      <subfield code="a">European Research Council [RIBOMYLOME_309545]; European Union&amp;apos;s Horizon 2020 research and innovation programme [727658, IASIS]; Spanish Ministry of Economy and Competitiveness [BFU2014-55054-P, BFU2017-86970-P]; Spanish Ministry of Economy and Competitiveness; ‘Centro de Excelencia Severo Ochoa 2013-2017’; CERCA Programme of the Generalitat de Catalunya; Marie Sklodowska-Curie Individual Fellowship from the European Union&amp;apos;s Horizon 2020 research and innovation programme (793135, ‘DeepRNA’ to B.L.). Funding for open access charge: European Research Council [RIBOMYLOME_309545], European Union [793135].</subfield>
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      <subfield code="a">RNAct: Protein-RNA interaction predictions for model organisms with supporting experimental data</subfield>
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