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.

10.1007/s13361-015-1228-5 http://scihub22266oqcxt.onion/10.1007/s13361-015-1228-5 C4607654!4607654 !26238326     free     free     free Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 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\26238326 .jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       J+Am+Soc+Mass+Spectrom 2015 ; 26 (11 ): 1858-64 Nephropedia Template TP {{tp|p=26238326 |t=2015. Using SEQUEST with theoretically complete sequence databases |pdf=|usr=}}{{26238326 }} gab.com Text Using SEQUEST with theoretically complete sequence databases JO: J Am Soc Mass Spectrom http://www.kidney.de/pget.php?&tw=1&pmid=26238326 #FOAvip SEQUEST has long been used to identify peptides/proteins from their tandem mass spectra and protein sequence databases. The algorithm has proven to be hugely successful for its sensitivity and specificity in identifying peptides/proteins, the sequences of which are present in the protein sequence databases. In this work, we report on work that attempts a new use for the algorithm by applying it to search a complete list of theoretically possible peptides, a de novo-like sequencing. We used freely available mass spectral data and determined a number of unique peptides as identified by SEQUEST. Using masses of these peptides and the mass accuracy of 0.001 Da, we have created a database of all theoretically possible peptide sequences corresponding to the precursor masses. We used our recently developed algorithm for determining all amino acid compositions corresponding to a mass interval, and used a lexicographic ordering to generate theoretical sequences from the compositions. The newly generated theoretical database was many-fold more complex than the original protein sequence database. We used SEQUEST to search and identify the best matches to the spectra from all theoretically possible peptide sequences. We found that SEQUEST cross-correlation score ranked the correct peptide match among the top sequence matches. The results testify to the high specificity of SEQUEST when combined with the high mass accuracy for intact peptides. Graphical Abstract ?. Twit Text FOAVip Using SEQUEST with theoretically complete sequence databases ????J Am Soc Mass Spectrom http://www.kidney.de/pget.php?&tw=1&pmid=26238326 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=26238326 #FOAvip English Wikipedia <ref>{{Cite pmid|26238326 }}</ref> Using SEQUEST with theoretically complete sequence databases #MMPMID26238326 Sadygov RG J Am Soc Mass Spectrom 2015[Nov]; 26 (11 ): 1858-64 PMID26238326 show ga SEQUEST has long been used to identify peptides/proteins from their tandem mass spectra and protein sequence databases. The algorithm has proven to be hugely successful for its sensitivity and specificity in identifying peptides/proteins, the sequences of which are present in the protein sequence databases. In this work, we report on work that attempts a new use for the algorithm by applying it to search a complete list of theoretically possible peptides, a de novo-like sequencing. We used freely available mass spectral data and determined a number of unique peptides as identified by SEQUEST. Using masses of these peptides and the mass accuracy of 0.001 Da, we have created a database of all theoretically possible peptide sequences corresponding to the precursor masses. We used our recently developed algorithm for determining all amino acid compositions corresponding to a mass interval, and used a lexicographic ordering to generate theoretical sequences from the compositions. The newly generated theoretical database was many-fold more complex than the original protein sequence database. We used SEQUEST to search and identify the best matches to the spectra from all theoretically possible peptide sequences. We found that SEQUEST cross-correlation score ranked the correct peptide match among the top sequence matches. The results testify to the high specificity of SEQUEST when combined with the high mass accuracy for intact peptides. Graphical Abstract ?. |*Databases, Protein [MESH] |*Software [MESH] |Proteomics/*methods [MESH]Using SEQUEST with theoretically complete sequence databases (epmc).pdf DeepDyve Pubget Overpricing