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@article{Zhang2007,
	Abstract = {Assembling peptides identified from LC-MS/MS spectra into a list of proteins is a critical step in analyzing shotgun proteomics data. As one peptide sequence can be mapped to multiple proteins in a database, na{\"\i}ve protein assembly can substantially overstate the number of proteins found in samples. We model the peptide-protein relationships in a bipartite graph and use efficient graph algorithms to identify protein clusters with shared peptides and to derive the minimal list of proteins. We test the effects of this parsimony analysis approach using MS/MS data sets generated from a defined human protein mixture, a yeast whole cell extract, and a human serum proteome after MARS column depletion. The results demonstrate that the bipartite parsimony technique not only simplifies protein lists but also improves the accuracy of protein identification. We use bipartite graphs for the visualization of the protein assembly results to render the parsimony analysis process transparent to users. Our approach also groups functionally related proteins together and improves the comprehensibility of the results. We have implemented the tool in the IDPicker package. The source code and binaries for this protein assembly pipeline are available under Mozilla Public License at the following URL: http://www.mc.vanderbilt.edu/msrc/bioinformatics/.},
	Author = {Zhang, Bing and Chambers, Matthew C. and Tabb, David L.},
	Date-Added = {2014-06-15 05:53:31 +0000},
	Date-Modified = {2014-06-15 05:53:31 +0000},
	Day = {04},
	Doi = {10.1021/pr070230d},
	Issn = {1535-3893},
	Journal = {Journal of proteome research},
	Keywords = {Reproducibility of Results},
	Language = {eng},
	Month = {Sep},
	Number = {9},
	Pages = {3549--3557},
	Title = {Proteomic parsimony through bipartite graph analysis improves accuracy and transparency.},
	Url = {http://www.ncbi.nlm.nih.gov/pubmed/17676885},
	Volume = {6},
	Year = {2007},
	Bdsk-Url-1 = {http://www.ncbi.nlm.nih.gov/pubmed/17676885},
	Bdsk-Url-2 = {http://dx.doi.org/10.1021/pr070230d}}



@article{Mayampurath2008,
	Abstract = {DeconMSn accurately determines the monoisotopic mass and charge state of parent ions from high-resolution tandem mass spectrometry data, offering significant improvement for LTQ_FT and LTQ_Orbitrap instruments over the commercially delivered Thermo Fisher Scientific's extract_msn tool. Optimal parent ion mass tolerance values can be determined using accurate mass information, thus improving peptide identifications for high-mass measurement accuracy experiments. For low-resolution data from LCQ and LTQ instruments, DeconMSn incorporates a support-vector-machine-based charge detection algorithm that identifies the most likely charge of a parent species through peak characteristics of its fragmentation pattern.http://ncrr.pnl.gov/software/ or http://www.proteomicsresource.org/.},
	Author = {Mayampurath, Anoop M. and Jaitly, Navdeep and Purvine, Samuel O. and Monroe, Matthew E. and Auberry, Kenneth J. and Adkins, Joshua N. and Smith, Richard D.},
	Doi = {10.1093/bioinformatics/btn063},
	Institution = {Pacific Northwest National Laboratory, Richland, WA 99354, USA.},
	Journal = {Bioinformatics},
	Keywords = {Algorithms; Artificial Intelligence; Pattern Recognition, Automated, methods; Reproducibility of Results; Sensitivity and Specificity; Software; Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization, methods},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Apr},
	Number = {7},
	Owner = {d3m629},
	Pages = {1021--1023},
	Pii = {btn063},
	Pmid = {18304935},
	Timestamp = {2014.04.03},
	Title = {DeconMSn: a software tool for accurate parent ion monoisotopic mass determination for tandem mass spectra.},
	Url = {http://dx.doi.org/10.1093/bioinformatics/btn063},
	Volume = {24},
	Year = {2008},
	Bdsk-Url-1 = {http://dx.doi.org/10.1093/bioinformatics/btn063}}


@article{Petyuk2010,
	Abstract = {Hybrid two-stage mass spectrometers capable of both highly accurate mass measurement and high throughput MS/MS fragmentation have become widely available in recent years, allowing for significantly better discrimination between true and false MS/MS peptide identifications by the application of a relatively narrow window for maximum allowable deviations of measured parent ion masses. To fully gain the advantage of highly accurate parent ion mass measurements, it is important to limit systematic mass measurement errors. Based on our previous studies of systematic biases in mass measurement errors, here, we have designed an algorithm and software tool that eliminates the systematic errors from the peptide ion masses in MS/MS data. We demonstrate that the elimination of the systematic mass measurement errors allows for the use of tighter criteria on the deviation of measured mass from theoretical monoisotopic peptide mass, resulting in a reduction of both false discovery and false negative rates of peptide identification. A software implementation of this algorithm called DtaRefinery reads a set of fragmentation spectra, searches for MS/MS peptide identifications using a FASTA file containing expected protein sequences, fits a regression model that can estimate systematic errors, and then corrects the parent ion mass entries by removing the estimated systematic error components. The output is a new file with fragmentation spectra with updated parent ion masses. The software is freely available.},
	Author = {Petyuk, Vladislav A. and Mayampurath, Anoop M. and Monroe, Matthew E. and Polpitiya, Ashoka D. and Purvine, Samuel O. and Anderson, Gordon A. and Camp, 2nd, David G and Smith, Richard D.},
	Doi = {10.1074/mcp.M900217-MCP200},
	Institution = {Biological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99352, USA.},
	Journal = {Mol Cell Proteomics},
	Keywords = {Algorithms; Amino Acid Sequence; Automatic Data Processing, methods; Databases, Protein; Peptides, analysis/chemistry; Proteomics, methods; Software Design; Tandem Mass Spectrometry, methods},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Mar},
	Number = {3},
	Owner = {D3M629},
	Pages = {486--496},
	Pii = {M900217-MCP200},
	Pmid = {20019053},
	Timestamp = {2014.03.24},
	Title = {DtaRefinery, a software tool for elimination of systematic errors from parent ion mass measurements in tandem mass spectra data sets.},
	Url = {http://dx.doi.org/10.1074/mcp.M900217-MCP200},
	Volume = {9},
	Year = {2010},
	Bdsk-Url-1 = {http://dx.doi.org/10.1074/mcp.M900217-MCP200}}

@article{Piehowski2013a,
	Abstract = {For bottom-up proteomics, there are wide variety of database-searching algorithms in use for matching peptide sequences to tandem MS spectra. Likewise, there are numerous strategies being employed to produce a confident list of peptide identifications from the different search algorithm outputs. Here we introduce a grid-search approach for determining optimal database filtering criteria in shotgun proteomics data analyses that is easily adaptable to any search. Systematic Trial and Error Parameter Selection--referred to as STEPS--utilizes user-defined parameter ranges to test a wide array of parameter combinations to arrive at an optimal "parameter set" for data filtering, thus maximizing confident identifications. The benefits of this approach in terms of numbers of true-positive identifications are demonstrated using datasets derived from immunoaffinity-depleted blood serum and a bacterial cell lysate, two common proteomics sample types.},
	Author = {Piehowski, Paul D. and Petyuk, Vladislav A. and Sandoval, John D. and Burnum, Kristin E. and Kiebel, Gary R. and Monroe, Matthew E. and Anderson, Gordon A. and Camp, 2nd, David G and Smith, Richard D.},
	Doi = {10.1002/pmic.201200096},
	Institution = {Biological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA99352, USA.},
	Journal = {Proteomics},
	Keywords = {Bacterial Proteins, analysis/chemistry; Blood Proteins, analysis/chemistry; Databases, Protein; Humans; Peptide Fragments, analysis/chemistry; Proteins, analysis/chemistry; Proteomics, methods; Shewanella; Tandem Mass Spectrometry, methods},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Mar},
	Number = {5},
	Owner = {D3M629},
	Pages = {766--770},
	Pmid = {23303698},
	Timestamp = {2014.03.24},
	Title = {STEPS: a grid search methodology for optimized peptide identification filtering of MS/MS database search results.},
	Url = {http://dx.doi.org/10.1002/pmic.201200096},
	Volume = {13},
	Year = {2013},
	Bdsk-Url-1 = {http://dx.doi.org/10.1002/pmic.201200096}}
