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10.1093/hmg/ddu019 http://scihub22266oqcxt.onion/10.1093/hmg/ddu019 C4014196!4014196!24436305     free     free     free Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Hum+Mol+Genet 2014 ; 23 (11): 3024-34 Nephropedia Template TP {{tp|p=24436305|t=2014. Impact of human pathogenic micro-insertions and micro-deletions on post-transcriptional regulation |pdf=|usr=}}{{24436305}} gab.com Text Impact of human pathogenic micro-insertions and micro-deletions on post-transcriptional regulation JO: Hum Mol Genet http://www.kidney.de/pget.php?&tw=1&pmid=24436305 #FOAvip Small insertions/deletions (INDELs) of ?21 bp comprise 18% of all recorded mutations causing human inherited disease and are evident in 24% of documented Mendelian diseases. INDELs affect gene function in multiple ways: for example, by introducing premature stop codons that either lead to the production of truncated proteins or affect transcriptional efficiency. However, the means by which they impact post-transcriptional regulation, including alternative splicing, have not been fully evaluated. In this study, we collate disease-causing INDELs from the Human Gene Mutation Database (HGMD) and neutral INDELs from the 1000 Genomes Project. The potential of these two types of INDELs to affect binding-site affinity of RNA-binding proteins (RBPs) was then evaluated. We identified several sequence features that can distinguish disease-causing INDELs from neutral INDELs. Moreover, we built a machine-learning predictor called PinPor (predicting pathogenic small insertions and deletions affecting post-transcriptional regulation, http://watson.compbio.iupui.edu/pinpor/) to ascertain which newly observed INDELs are likely to be pathogenic. Our results show that disease-causing INDELs are more likely to ablate RBP-binding sites and tend to affect more RBP-binding sites than neutral INDELs. Additionally, disease-causing INDELs give rise to greater deviations in binding affinity than neutral INDELs. We also demonstrated that disease-causing INDELs may be distinguished from neutral INDELs by several sequence features, such as their proximity to splice sites and their potential effects on RNA secondary structure. This predictor showed satisfactory performance in identifying numerous pathogenic INDELs, with a Matthews correlation coefficient (MCC) value of 0.51 and an accuracy of 0.75. Twit Text FOAVip Impact of human pathogenic micro-insertions and micro-deletions on post-transcriptional regulation ????Hum Mol Genet http://www.kidney.de/pget.php?&tw=1&pmid=24436305 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=24436305 #FOAvip English Wikipedia <ref>{{Cite pmid|24436305}}</ref> Impact of human pathogenic micro-insertions and micro-deletions on post-transcriptional regulation #MMPMID24436305 Zhang X; Lin H; Zhao H; Hao Y; Mort M; Cooper DN; Zhou Y; Liu Y Hum Mol Genet 2014[Jun]; 23 (11): 3024-34 PMID24436305show ga Small insertions/deletions (INDELs) of ?21 bp comprise 18% of all recorded mutations causing human inherited disease and are evident in 24% of documented Mendelian diseases. INDELs affect gene function in multiple ways: for example, by introducing premature stop codons that either lead to the production of truncated proteins or affect transcriptional efficiency. However, the means by which they impact post-transcriptional regulation, including alternative splicing, have not been fully evaluated. In this study, we collate disease-causing INDELs from the Human Gene Mutation Database (HGMD) and neutral INDELs from the 1000 Genomes Project. The potential of these two types of INDELs to affect binding-site affinity of RNA-binding proteins (RBPs) was then evaluated. We identified several sequence features that can distinguish disease-causing INDELs from neutral INDELs. Moreover, we built a machine-learning predictor called PinPor (predicting pathogenic small insertions and deletions affecting post-transcriptional regulation, http://watson.compbio.iupui.edu/pinpor/) to ascertain which newly observed INDELs are likely to be pathogenic. Our results show that disease-causing INDELs are more likely to ablate RBP-binding sites and tend to affect more RBP-binding sites than neutral INDELs. Additionally, disease-causing INDELs give rise to greater deviations in binding affinity than neutral INDELs. We also demonstrated that disease-causing INDELs may be distinguished from neutral INDELs by several sequence features, such as their proximity to splice sites and their potential effects on RNA secondary structure. This predictor showed satisfactory performance in identifying numerous pathogenic INDELs, with a Matthews correlation coefficient (MCC) value of 0.51 and an accuracy of 0.75. äImpact of human pathogenic micro-insertions and micro-deletions on pos(epmc).pdf DeepDyve Pubget Overpricing