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10.1007/s12551-014-0145-3 http://scihub22266oqcxt.onion/10.1007/s12551-014-0145-3 C5418423!5418423!28509974     free     free     free Deprecated: Implicit conversion from float 227.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 227.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 227.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 227.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Biophys+Rev 2015 ; 7 (1): 141-59 Nephropedia Template TP {{tp|p=28509974|t=2015. Decoding the complex genetic causes of heart diseases using systems biology |pdf=|usr=}}{{28509974}} gab.com Text Decoding the complex genetic causes of heart diseases using systems biology JO: Biophys Rev http://www.kidney.de/pget.php?&tw=1&pmid=28509974 #FOAvip The pace of disease gene discovery is still much slower than expected, even with the use of cost-effective DNA sequencing and genotyping technologies. It is increasingly clear that many inherited heart diseases have a more complex polygenic aetiology than previously thought. Understanding the role of gene?gene interactions, epigenetics, and non-coding regulatory regions is becoming increasingly critical in predicting the functional consequences of genetic mutations identified by genome-wide association studies and whole-genome or exome sequencing. A systems biology approach is now being widely employed to systematically discover genes that are involved in heart diseases in humans or relevant animal models through bioinformatics. The overarching premise is that the integration of high-quality causal gene regulatory networks (GRNs), genomics, epigenomics, transcriptomics and other genome-wide data will greatly accelerate the discovery of the complex genetic causes of congenital and complex heart diseases. This review summarises state-of-the-art genomic and bioinformatics techniques that are used in accelerating the pace of disease gene discovery in heart diseases. Accompanying this review, we provide an interactive web-resource for systems biology analysis of mammalian heart development and diseases, CardiacCode (http://CardiacCode.victorchang.edu.au/). CardiacCode features a dataset of over 700 pieces of manually curated genetic or molecular perturbation data, which enables the inference of a cardiac-specific GRN of 280 regulatory relationships between 33 regulator genes and 129 target genes. We believe this growing resource will fill an urgent unmet need to fully realise the true potential of predictive and personalised genomic medicine in tackling human heart disease.Electronic supplementary material: The online version of this article (doi:10.1007/s12551-014-0145-3) contains supplementary material, which is available to authorized users. Twit Text FOAVip Decoding the complex genetic causes of heart diseases using systems biology ????Biophys Rev http://www.kidney.de/pget.php?&tw=1&pmid=28509974 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=28509974 #FOAvip English Wikipedia <ref>{{Cite pmid|28509974}}</ref> Decoding the complex genetic causes of heart diseases using systems biology #MMPMID28509974 Djordjevic D; Deshpande V; Szczesnik T; Yang A; Humphreys DT; Giannoulatou E; Ho JWK Biophys Rev 2015[Mar]; 7 (1): 141-59 PMID28509974show ga The pace of disease gene discovery is still much slower than expected, even with the use of cost-effective DNA sequencing and genotyping technologies. It is increasingly clear that many inherited heart diseases have a more complex polygenic aetiology than previously thought. Understanding the role of gene?gene interactions, epigenetics, and non-coding regulatory regions is becoming increasingly critical in predicting the functional consequences of genetic mutations identified by genome-wide association studies and whole-genome or exome sequencing. A systems biology approach is now being widely employed to systematically discover genes that are involved in heart diseases in humans or relevant animal models through bioinformatics. The overarching premise is that the integration of high-quality causal gene regulatory networks (GRNs), genomics, epigenomics, transcriptomics and other genome-wide data will greatly accelerate the discovery of the complex genetic causes of congenital and complex heart diseases. This review summarises state-of-the-art genomic and bioinformatics techniques that are used in accelerating the pace of disease gene discovery in heart diseases. Accompanying this review, we provide an interactive web-resource for systems biology analysis of mammalian heart development and diseases, CardiacCode (http://CardiacCode.victorchang.edu.au/). CardiacCode features a dataset of over 700 pieces of manually curated genetic or molecular perturbation data, which enables the inference of a cardiac-specific GRN of 280 regulatory relationships between 33 regulator genes and 129 target genes. We believe this growing resource will fill an urgent unmet need to fully realise the true potential of predictive and personalised genomic medicine in tackling human heart disease.Electronic supplementary material: The online version of this article (doi:10.1007/s12551-014-0145-3) contains supplementary material, which is available to authorized users. äDecoding the complex genetic causes of heart diseases using systems bi(epmc).pdf DeepDyve Pubget Overpricing