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10.1098/rsif.2015.0573 http://scihub22266oqcxt.onion/10.1098/rsif.2015.0573 C4614467!4614467 !26333811     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 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 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 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Warning: imagejpeg(C:\Inetpub\vhosts\kidney.de\httpdocs\phplern\26333811 .jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       J+R+Soc+Interface 2015 ; 12 (110 ): 0573 Nephropedia Template TP {{tp|p=26333811 |t=2015. Quantifying noise in mass spectrometry and yeast two-hybrid protein interaction detection experiments |pdf=|usr=}}{{26333811 }} gab.com Text Quantifying noise in mass spectrometry and yeast two-hybrid protein interaction detection experiments JO: J R Soc Interface http://www.kidney.de/pget.php?&tw=1&pmid=26333811 #FOAvip Protein interaction networks (PINs) are popular means to visualize the proteome. However, PIN datasets are known to be noisy, incomplete and biased by the experimental protocols used to detect protein interactions. This paper aims at understanding the connection between true protein interactions and the protein interaction datasets that have been obtained using the most popular experimental techniques, i.e. mass spectronomy and yeast two-hybrid. We start from the observation that the adjacency matrix of a PIN, i.e. the binary matrix which defines, for every pair of proteins in the network, whether or not there is a link, has a special form, that we call separable. This induces precise relationships between the moments of the degree distribution (i.e. the average number of links that a protein in the network has, its variance, etc.) and the number of short loops (i.e. triangles, squares, etc.) along the links of the network. These relationships provide powerful tools to test the reliability of datasets and hint at the underlying biological mechanism with which proteins and complexes recruit each other. Twit Text FOAVip Quantifying noise in mass spectrometry and yeast two-hybrid protein interaction detection experiments ????J R Soc Interface http://www.kidney.de/pget.php?&tw=1&pmid=26333811 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=26333811 #FOAvip English Wikipedia <ref>{{Cite pmid|26333811 }}</ref> Quantifying noise in mass spectrometry and yeast two-hybrid protein interaction detection experiments #MMPMID26333811 Annibale A ; Coolen AC ; Planell-Morell N J R Soc Interface 2015[Sep]; 12 (110 ): 0573 PMID26333811 show ga Protein interaction networks (PINs) are popular means to visualize the proteome. However, PIN datasets are known to be noisy, incomplete and biased by the experimental protocols used to detect protein interactions. This paper aims at understanding the connection between true protein interactions and the protein interaction datasets that have been obtained using the most popular experimental techniques, i.e. mass spectronomy and yeast two-hybrid. We start from the observation that the adjacency matrix of a PIN, i.e. the binary matrix which defines, for every pair of proteins in the network, whether or not there is a link, has a special form, that we call separable. This induces precise relationships between the moments of the degree distribution (i.e. the average number of links that a protein in the network has, its variance, etc.) and the number of short loops (i.e. triangles, squares, etc.) along the links of the network. These relationships provide powerful tools to test the reliability of datasets and hint at the underlying biological mechanism with which proteins and complexes recruit each other. |*Mass Spectrometry [MESH] |*Saccharomyces cerevisiae/genetics/metabolism [MESH] |*Signal-To-Noise Ratio [MESH]Quantifying noise in mass spectrometry and yeast two-hybrid protein in(epmc).pdf DeepDyve Pubget Overpricing