Use my Search Websuite to scan PubMed, PMCentral, Journal Hosts and Journal Archives, FullText. Kick-your-searchterm to multiple Engines kick-your-query now !>

A dictionary by aggregated review articles of nephrology, medicine and the life sciences Your one-stop-run pathway from word to the immediate pdf of peer-reviewed on-topic knowledge.

10.1093/nar/gkx210 http://scihub22266oqcxt.onion/10.1093/nar/gkx210 C5435932!5435932!28379430     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Nucleic+Acids+Res 2017 ; 45 (9): 5048-60 Nephropedia Template TP {{tp|p=28379430|t=2017. Enhancing identification of cancer types via lowly-expressed microRNAs |pdf=|usr=}}{{28379430}} gab.com Text Enhancing identification of cancer types via lowly-expressed microRNAs JO: Nucleic Acids Res http://www.kidney.de/pget.php?&tw=1&pmid=28379430 #FOAvip The primary function of microRNAs (miRNAs) is to maintain cell homeostasis. In cancerous tissues miRNAs? expression undergo drastic alterations. In this study, we use miRNA expression profiles from The Cancer Genome Atlas of 24 cancer types and 3 healthy tissues, collected from >8500 samples. We seek to classify the cancer's origin and tissue identification using the expression from 1046 reported miRNAs. Despite an apparent uniform appearance of miRNAs among cancerous samples, we recover indispensable information from lowly expressed miRNAs regarding the cancer/tissue types. Multiclass support vector machine classification yields an average recall of 58% in identifying the correct tissue and tumor types. Data discretization had led to substantial improvement, reaching an average recall of 91% (95% median). We propose a straightforward protocol as a crucial step in classifying tumors of unknown primary origin. Our counter-intuitive conclusion is that in almost all cancer types, highly expressing miRNAs mask the significant signal that lower expressed miRNAs provide. Twit Text FOAVip Enhancing identification of cancer types via lowly-expressed microRNAs ????Nucleic Acids Res http://www.kidney.de/pget.php?&tw=1&pmid=28379430 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=28379430 #FOAvip English Wikipedia <ref>{{Cite pmid|28379430}}</ref> Enhancing identification of cancer types via lowly-expressed microRNAs #MMPMID28379430 Rasnic R; Linial N; Linial M Nucleic Acids Res 2017[May]; 45 (9): 5048-60 PMID28379430show ga The primary function of microRNAs (miRNAs) is to maintain cell homeostasis. In cancerous tissues miRNAs? expression undergo drastic alterations. In this study, we use miRNA expression profiles from The Cancer Genome Atlas of 24 cancer types and 3 healthy tissues, collected from >8500 samples. We seek to classify the cancer's origin and tissue identification using the expression from 1046 reported miRNAs. Despite an apparent uniform appearance of miRNAs among cancerous samples, we recover indispensable information from lowly expressed miRNAs regarding the cancer/tissue types. Multiclass support vector machine classification yields an average recall of 58% in identifying the correct tissue and tumor types. Data discretization had led to substantial improvement, reaching an average recall of 91% (95% median). We propose a straightforward protocol as a crucial step in classifying tumors of unknown primary origin. Our counter-intuitive conclusion is that in almost all cancer types, highly expressing miRNAs mask the significant signal that lower expressed miRNAs provide. äEnhancing identification of cancer types via lowly-expressed microRNAs(epmc).pdf DeepDyve Pubget Overpricing