Chromatogram libraries improve peptide detection and quantification by data independent acquisition mass spectrometry von Searle, Brian C., Pino, Lindsay K., Egertson, Jarrett D., Ting, Ying S., Lawrence, Robert T., MacLean, Brendan X., Villén, Judit, MacCoss, Michael J.

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MSstats: an R package for statistical analysis of quantitative mass spectrometry-based proteomic experiments von Choi, Meena, Chang, Ching-Yun, Clough, Timothy, Broudy, Daniel, Killeen, Trevor, MacLean, Brendan, Vitek, Olga

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The Skyline ecosystem: Informatics for quantitative mass spectrometry proteomics von Pino, Lindsay K., Searle, Brian C., Bollinger, James G., Nunn, Brook, MacLean, Brendan, MacCoss, Michael J.

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Improving Precursor Selectivity in Data-Independent Acquisition Using Overlapping Windows von Amodei, Dario, Egertson, Jarrett, MacLean, Brendan X., Johnson, Richard, Merrihew, Gennifer E., Keller, Austin, Marsh, Don, Vitek, Olga, Mallick, Parag, MacCoss, Michael J.

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Skyline for Small Molecules: A Unifying Software Package for Quantitative Metabolomics von Adams, Kendra J, Pratt, Brian, Bose, Neelanjan, Dubois, Laura G, St. John-Williams, Lisa, Perrott, Kevin M, Ky, Karina, Kapahi, Pankaj, Sharma, Vagisha, MacCoss, Michael J, Moseley, M. Arthur, Colton, Carol A, MacLean, Brendan X, Schilling, Birgit, Thompson, J. Will

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The ProteomeXchange consortium at 10 years: 2023 update von Deutsch, Eric W, Bandeira, Nuno, Perez-Riverol, Yasset, Sharma, Vagisha, Carver, Jeremy J, Mendoza, Luis, Kundu, Deepti J, Wang, Shengbo, Bandla, Chakradhar, Kamatchinathan, Selvakumar, Hewapathirana, Suresh, Pullman, Benjamin S, Wertz, Julie, Sun, Zhi, Kawano, Shin, Okuda, Shujiro, Watanabe, Yu, MacLean, Brendan, MacCoss, Michael J, Zhu, Yunping, Ishihama, Yasushi, Vizcaíno, Juan Antonio

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The ProteomeXchange consortium in 2020: enabling ‘big data’ approaches in proteomics von Deutsch, Eric W, Bandeira, Nuno, Sharma, Vagisha, Perez-Riverol, Yasset, Carver, Jeremy J, Kundu, Deepti J, García-Seisdedos, David, Jarnuczak, Andrew F, Hewapathirana, Suresh, Pullman, Benjamin S, Wertz, Julie, Sun, Zhi, Kawano, Shin, Okuda, Shujiro, Watanabe, Yu, Hermjakob, Henning, MacLean, Brendan, MacCoss, Michael J, Zhu, Yunping, Ishihama, Yasushi, Vizcaíno, Juan A

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Standardization of PGC-LC-MS-based glycomics for sample specific glycotyping von Ashwood, Christopher, Pratt, Brian, MacLean, Brendan X, Gundry, Rebekah L, Packer, Nicolle H

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Using iRT, a normalized retention time for more targeted measurement of peptides von Escher, Claudia, Reiter, Lukas, MacLean, Brendan, Ossola, Reto, Herzog, Franz, Chilton, John, MacCoss, Michael J., Rinner, Oliver

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Panorama Public: A Public Repository for Quantitative Data Sets Processed in Skyline von Sharma, Vagisha, Eckels, Josh, Schilling, Birgit, Ludwig, Christina, Jaffe, Jacob D., MacCoss, Michael J., MacLean, Brendan

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Skyline: an open source document editor for creating and analyzing targeted proteomics experiments von MacLean, Brendan, Tomazela, Daniela M., Shulman, Nicholas, Chambers, Matthew, Finney, Gregory L., Frewen, Barbara, Kern, Randall, Tabb, David L., Liebler, Daniel C., MacCoss, Michael J.

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Utilizing Skyline to analyze lipidomics data containing liquid chromatography, ion mobility spectrometry and mass spectrometry dimensions von Kirkwood, Kaylie I., Pratt, Brian S., Shulman, Nicholas, Tamura, Kaipo, MacCoss, Michael J., MacLean, Brendan X., Baker, Erin S.

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Building high-quality assay libraries for targeted analysis of SWATH MS data von Schubert, Olga T, Gillet, Ludovic C, Collins, Ben C, Navarro, Pedro, Rosenberger, George, Wolski, Witold E, Lam, Henry, Amodei, Dario, Mallick, Parag, MacLean, Brendan, Aebersold, Ruedi

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MSstats Version 4.0: Statistical Analyses of Quantitative Mass Spectrometry-Based Proteomic Experiments with Chromatography-Based Quantification at Scale von Kohler, Devon, Staniak, Mateusz, Tsai, Tsung-Heng, Huang, Ting, Shulman, Nicholas, Bernhardt, Oliver M., MacLean, Brendan X., Nesvizhskii, Alexey I., Reiter, Lukas, Sabido, Eduard, Choi, Meena, Vitek, Olga

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Statistical control of peptide and protein error rates in large-scale targeted data-independent acquisition analyses von Rosenberger, George, Bludau, Isabell, Schmitt, Uwe, Heusel, Moritz, Hunter, Christie L, Liu, Yansheng, MacCoss, Michael J, MacLean, Brendan X, Nesvizhskii, Alexey I, Pedrioli, Patrick G A, Reiter, Lukas, Röst, Hannes L, Tate, Stephen, Ting, Ying S, Collins, Ben C, Aebersold, Ruedi

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A cross-platform toolkit for mass spectrometry and proteomics von Chambers, Matthew C, Maclean, Brendan, Burke, Robert, Amodei, Dario, Ruderman, Daniel L, Neumann, Steffen, Gatto, Laurent, Fischer, Bernd, Pratt, Brian, Egertson, Jarrett, Hoff, Katherine, Kessner, Darren, Tasman, Natalie, Shulman, Nicholas, Frewen, Barbara, Baker, Tahmina A, Brusniak, Mi-Youn, Paulse, Christopher, Creasy, David, Flashner, Lisa, Kani, Kian, Moulding, Chris, Seymour, Sean L, Nuwaysir, Lydia M, Lefebvre, Brent, Kuhlmann, Frank, Roark, Joe, Rainer, Paape, Detlev, Suckau, Hemenway, Tina, Huhmer, Andreas, Langridge, James, Connolly, Brian, Chadick, Trey, Holly, Krisztina, Eckels, Josh, Deutsch, Eric W, Moritz, Robert L, Katz, Jonathan E, Agus, David B, MacCoss, Michael, Tabb, David L, Mallick, Parag

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Multiplexed MS/MS for improved data-independent acquisition von Egertson, Jarrett D, Kuehn, Andreas, Merrihew, Gennifer E, Bateman, Nicholas W, MacLean, Brendan X, Ting, Ying S, Canterbury, Jesse D, Marsh, Donald M, Kellmann, Markus, Zabrouskov, Vlad, Wu, Christine C, MacCoss, Michael J

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Evaluating the Performance of the Astral Mass Analyzer for Quantitative Proteomics Using Data-Independent Acquisition von Heil, Lilian R., Damoc, Eugen, Arrey, Tabiwang N., Pashkova, Anna, Denisov, Eduard, Petzoldt, Johannes, Peterson, Amelia C., Hsu, Chris, Searle, Brian C., Shulman, Nicholas, Riffle, Michael, Connolly, Brian, MacLean, Brendan X., Remes, Philip M., Senko, Michael W., Stewart, Hamish I., Hock, Christian, Makarov, Alexander A., Hermanson, Daniel, Zabrouskov, Vlad, Wu, Christine C., MacCoss, Michael J.

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Using Skyline to Analyze Data-Containing Liquid Chromatography, Ion Mobility Spectrometry, and Mass Spectrometry Dimensions von MacLean, Brendan X., Pratt, Brian S., Egertson, Jarrett D., MacCoss, Michael J., Smith, Richard D., Baker, Erin S.

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Selection of Features with Consistent Profiles Improves Relative Protein Quantification in Mass Spectrometry Experiments von Tsai, Tsung-Heng, Choi, Meena, Banfai, Balazs, Liu, Yansheng, MacLean, Brendan X., Dunkley, Tom, Vitek, Olga

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