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10.3389/fgene.2020.574485 http://scihub22266oqcxt.onion/10.3389/fgene.2020.574485 33193680!7649352!33193680     free     free     free Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Front+Genet 2020 ; 11 (ä): 574485 Nephropedia Template TP {{tp|p=33193680|t=2020. Advances in RNA 3D Structure Modeling Using Experimental Data |pdf=|usr=}}{{33193680}} gab.com Text Advances in RNA 3D Structure Modeling Using Experimental Data JO: Front Genet http://www.kidney.de/pget.php?&tw=1&pmid=33193680 #FOAvip RNA is a unique bio-macromolecule that can both record genetic information and perform biological functions in a variety of molecular processes, including transcription, splicing, translation, and even regulating protein function. RNAs adopt specific three-dimensional conformations to enable their functions. Experimental determination of high-resolution RNA structures using x-ray crystallography is both laborious and demands expertise, thus, hindering our comprehension of RNA structural biology. The computational modeling of RNA structure was a milestone in the birth of bioinformatics. Although computational modeling has been greatly improved over the last decade showing many successful cases, the accuracy of such computational modeling is not only length-dependent but also varies according to the complexity of the structure. To increase credibility, various experimental data were integrated into computational modeling. In this review, we summarize the experiments that can be integrated into RNA structure modeling as well as the computational methods based on these experimental data. We also demonstrate how computational modeling can help the experimental determination of RNA structure. We highlight the recent advances in computational modeling which can offer reliable structure models using high-throughput experimental data. Twit Text FOAVip Advances in RNA 3D Structure Modeling Using Experimental Data ????Front Genet http://www.kidney.de/pget.php?&tw=1&pmid=33193680 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33193680 #FOAvip English Wikipedia <ref>{{Cite pmid|33193680}}</ref> Advances in RNA 3D Structure Modeling Using Experimental Data #MMPMID33193680 Li B; Cao Y; Westhof E; Miao Z Front Genet 2020[]; 11 (ä): 574485 PMID33193680show ga RNA is a unique bio-macromolecule that can both record genetic information and perform biological functions in a variety of molecular processes, including transcription, splicing, translation, and even regulating protein function. RNAs adopt specific three-dimensional conformations to enable their functions. Experimental determination of high-resolution RNA structures using x-ray crystallography is both laborious and demands expertise, thus, hindering our comprehension of RNA structural biology. The computational modeling of RNA structure was a milestone in the birth of bioinformatics. Although computational modeling has been greatly improved over the last decade showing many successful cases, the accuracy of such computational modeling is not only length-dependent but also varies according to the complexity of the structure. To increase credibility, various experimental data were integrated into computational modeling. In this review, we summarize the experiments that can be integrated into RNA structure modeling as well as the computational methods based on these experimental data. We also demonstrate how computational modeling can help the experimental determination of RNA structure. We highlight the recent advances in computational modeling which can offer reliable structure models using high-throughput experimental data. äAdvances in RNA 3D Structure Modeling Using Experimental Data (epmc).pdf DeepDyve Pubget Overpricing