Proteogenomics: concepts, applications and computational strategies von Nesvizhskii, Alexey I

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A survey of computational methods and error rate estimation procedures for peptide and protein identification in shotgun proteomics von Nesvizhskii, Alexey I.

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dia-PASEF data analysis using FragPipe and DIA-NN for deep proteomics of low sample amounts von Demichev, Vadim, Szyrwiel, Lukasz, Yu, Fengchao, Teo, Guo Ci, Rosenberger, George, Niewienda, Agathe, Ludwig, Daniela, Decker, Jens, Kaspar-Schoenefeld, Stephanie, Lilley, Kathryn S., Mülleder, Michael, Nesvizhskii, Alexey I., Ralser, Markus

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Fast Deisotoping Algorithm and Its Implementation in the MSFragger Search Engine von Teo, Guo Ci, Polasky, Daniel A, Yu, Fengchao, Nesvizhskii, Alexey I

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MSBooster: improving peptide identification rates using deep learning-based features von Yang, Kevin L., Yu, Fengchao, Teo, Guo Ci, Li, Kai, Demichev, Vadim, Ralser, Markus, Nesvizhskii, Alexey I.

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Identification of modified peptides using localization-aware open search von Yu, Fengchao, Teo, Guo Ci, Kong, Andy T., Haynes, Sarah E., Avtonomov, Dmitry M., Geiszler, Daniel J., Nesvizhskii, Alexey I.

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DIA-Umpire: comprehensive computational framework for data-independent acquisition proteomics von Tsou, Chih-Chiang, Avtonomov, Dmitry, Larsen, Brett, Tucholska, Monika, Choi, Hyungwon, Gingras, Anne-Claude, Nesvizhskii, Alexey I

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Analysis and validation of proteomic data generated by tandem mass spectrometry von Nesvizhskii, Alexey I, Vitek, Olga, Aebersold, Ruedi

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Analysis of DIA proteomics data using MSFragger-DIA and FragPipe computational platform von Yu, Fengchao, Teo, Guo Ci, Kong, Andy T., Fröhlich, Klemens, Li, Ginny Xiaohe, Demichev, Vadim, Nesvizhskii, Alexey I.

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Targeting SWI/SNF ATPases in enhancer-addicted prostate cancer von Xiao, Lanbo, Parolia, Abhijit, Qiao, Yuanyuan, Bawa, Pushpinder, Eyunni, Sanjana, Mannan, Rahul, Carson, Sandra E., Chang, Yu, Wang, Xiaoju, Zhang, Yuping, Vo, Josh N., Kregel, Steven, Simko, Stephanie A., Delekta, Andrew D., Jaber, Mustapha, Zheng, Heng, Apel, Ingrid J., McMurry, Lisa, Su, Fengyun, Wang, Rui, Zelenka-Wang, Sylvia, Sasmal, Sanjita, Khare, Leena, Mukherjee, Subhendu, Abbineni, Chandrasekhar, Aithal, Kiran, Bhakta, Mital S., Ghurye, Jay, Cao, Xuhong, Navone, Nora M., Nesvizhskii, Alexey I., Mehra, Rohit, Vaishampayan, Ulka, Blanchette, Marco, Wang, Yuzhuo, Samajdar, Susanta, Ramachandra, Murali, Chinnaiyan, Arul M.

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BioContainers: an open-source and community-driven framework for software standardization von da Veiga Leprevost, Felipe, Grüning, Björn A, Alves Aflitos, Saulo, Röst, Hannes L, Uszkoreit, Julian, Barsnes, Harald, Vaudel, Marc, Moreno, Pablo, Gatto, Laurent, Weber, Jonas, Bai, Mingze, Jimenez, Rafael C, Sachsenberg, Timo, Pfeuffer, Julianus, Vera Alvarez, Roberto, Griss, Johannes, Nesvizhskii, Alexey I, Perez-Riverol, Yasset

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Significance Analysis of Spectral Count Data in Label-free Shotgun Proteomics von Choi, Hyungwon, Fermin, Damian, Nesvizhskii, Alexey I.

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ProHits-viz: a suite of web tools for visualizing interaction proteomics data von Knight, James D R, Choi, Hyungwon, Gupta, Gagan D, Pelletier, Laurence, Raught, Brian, Nesvizhskii, Alexey I, Gingras, Anne-Claude

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iProphet: Multi-level Integrative Analysis of Shotgun Proteomic Data Improves Peptide and Protein Identification Rates and Error Estimates von Shteynberg, David, Deutsch, Eric W., Lam, Henry, Eng, Jimmy K., Sun, Zhi, Tasman, Natalie, Mendoza, Luis, Moritz, Robert L., Aebersold, Ruedi, Nesvizhskii, Alexey I.

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Detecting diagnostic features in MS/MS spectra of post-translationally modified peptides von Geiszler, Daniel J., Polasky, Daniel A., Yu, Fengchao, Nesvizhskii, Alexey I.

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Quantitative proteomic landscape of metaplastic breast carcinoma pathological subtypes and their relationship to triple-negative tumors von Djomehri, Sabra I., Gonzalez, Maria E., da Veiga Leprevost, Felipe, Tekula, Shilpa R., Chang, Hui-Yin, White, Marissa J., Cimino-Mathews, Ashley, Burman, Boris, Basrur, Venkatesha, Argani, Pedram, Nesvizhskii, Alexey I., Kleer, Celina G.

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SAINT: probabilistic scoring of affinity purification–mass spectrometry data von Choi, Hyungwon, Larsen, Brett, Lin, Zhen-Yuan, Breitkreutz, Ashton, Mellacheruvu, Dattatreya, Fermin, Damian, Qin, Zhaohui S, Tyers, Mike, Gingras, Anne-Claude, Nesvizhskii, Alexey I

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A statistical model-building perspective to identification of MS/MS spectra with PeptideProphet von Ma, Kelvin, Vitek, Olga, Nesvizhskii, Alexey I

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guided tour of the Trans-Proteomic Pipeline von Deutsch, Eric W, Mendoza, Luis, Shteynberg, David, Farrah, Terry, Lam, Henry, Tasman, Natalie, Sun, Zhi, Nilsson, Erik, Pratt, Brian, Prazen, Bryan, Eng, Jimmy K, Martin, Daniel B, Nesvizhskii, Alexey I, Aebersold, Ruedi

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A data-independent acquisition-based global phosphoproteomics system enables deep profiling von Kitata, Reta Birhanu, Choong, Wai-Kok, Tsai, Chia-Feng, Lin, Pei-Yi, Chen, Bo-Shiun, Chang, Yun-Chien, Nesvizhskii, Alexey I., Sung, Ting-Yi, Chen, Yu-Ju

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