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Improvements to the Percolator Algorithm for Peptide Identification from Shotgun Proteomics Data Sets

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NEC Labs America, Princeton, New Jersey 08540, Computer Science Department, New York University, New York, New York 10003, Department of Genome Sciences, University of Washington, Seattle, Washington 98195, Center for Biomembrane Research, Department of Biochemistry and Biophysics, Stockholm University, Sweden, and Department of Computer Science and Engineering, University of Washington, Seattle, Washington 98195
* To whom correspondence should be addressed. E-mail: [email protected]
†NEC Research.
⊥New York University.
‡Department of Genome Sciences, University of Washington.
§Stockholm University.
∥Department of Computer Science and Engineering, University of Washington.
Cite this: J. Proteome Res. 2009, 8, 7, 3737–3745
Publication Date (Web):April 23, 2009
https://doi.org/10.1021/pr801109k
Copyright © 2009 American Chemical Society

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    Abstract

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    Shotgun proteomics coupled with database search software allows the identification of a large number of peptides in a single experiment. However, some existing search algorithms, such as SEQUEST, use score functions that are designed primarily to identify the best peptide for a given spectrum. Consequently, when comparing identifications across spectra, the SEQUEST score function Xcorr fails to discriminate accurately between correct and incorrect peptide identifications. Several machine learning methods have been proposed to address the resulting classification task of distinguishing between correct and incorrect peptide-spectrum matches (PSMs). A recent example is Percolator, which uses semisupervised learning and a decoy database search strategy to learn to distinguish between correct and incorrect PSMs identified by a database search algorithm. The current work describes three improvements to Percolator. (1) Percolator’s heuristic optimization is replaced with a clear objective function, with intuitive reasons behind its choice. (2) Tractable nonlinear models are used instead of linear models, leading to improved accuracy over the original Percolator. (3) A method, Q-ranker, for directly optimizing the number of identified spectra at a specified q value is proposed, which achieves further gains.

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    12. Paolo Cifani, Avantika Dhabaria, Zining Chen, Akihide Yoshimi, Emily Kawaler, Omar Abdel-Wahab, John T. Poirier, Alex Kentsis. ProteomeGenerator: A Framework for Comprehensive Proteomics Based on de Novo Transcriptome Assembly and High-Accuracy Peptide Mass Spectral Matching. Journal of Proteome Research 2018, 17 (11) , 3681-3692. https://doi.org/10.1021/acs.jproteome.8b00295
    13. John D. Lapek, Jr., Ronnie H. Fang, Xiaoli Wei, Pengyang Li, Bo Wang, Liangfang Zhang, and David J. Gonzalez . Biomimetic Virulomics for Capture and Identification of Cell-Type Specific Effector Proteins. ACS Nano 2017, 11 (12) , 11831-11838. https://doi.org/10.1021/acsnano.7b02650
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    16. Christopher S. Hughes, Chenchen Zhu, Victor Spicer, Oleg V. Krokhin, and Gregg B. Morin . Evaluating the Characteristics of Reporter Ion Signal Acquired in the Orbitrap Analyzer for Isobaric Mass Tag Proteome Quantification Experiments. Journal of Proteome Research 2017, 16 (5) , 1831-1838. https://doi.org/10.1021/acs.jproteome.7b00092
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    20. Chengjian Tu, Quanhu Sheng, Jun Li, Danjun Ma, Xiaomeng Shen, Xue Wang, Yu Shyr, Zhengping Yi, and Jun Qu . Optimization of Search Engines and Postprocessing Approaches to Maximize Peptide and Protein Identification for High-Resolution Mass Data. Journal of Proteome Research 2015, 14 (11) , 4662-4673. https://doi.org/10.1021/acs.jproteome.5b00536
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    23. Lucrece Matheron, Henk van den Toorn, Albert J. R. Heck, and Shabaz Mohammed . Characterization of Biases in Phosphopeptide Enrichment by Ti4+-Immobilized Metal Affinity Chromatography and TiO2 Using a Massive Synthetic Library and Human Cell Digests. Analytical Chemistry 2014, 86 (16) , 8312-8320. https://doi.org/10.1021/ac501803z
    24. Srikanth Srinivas Manda, Raja Sekhar Nirujogi, Sneha Maria Pinto, Min-Sik Kim, Keshava K. Datta, Ravi Sirdeshmukh, T. S. Keshava Prasad, Visith Thongboonkerd, Akhilesh Pandey, and Harsha Gowda . Identification and Characterization of Proteins Encoded by Chromosome 12 as Part of Chromosome-centric Human Proteome Project. Journal of Proteome Research 2014, 13 (7) , 3166-3177. https://doi.org/10.1021/pr401123v
    25. Clarissa Dickhut, Ingo Feldmann, Jörg Lambert, and René P. Zahedi . Impact of Digestion Conditions on Phosphoproteomics. Journal of Proteome Research 2014, 13 (6) , 2761-2770. https://doi.org/10.1021/pr401181y
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    30. Yaoyang Zhang, Bryan R. Fonslow, Bing Shan, Moon-Chang Baek, and John R. Yates, III . Protein Analysis by Shotgun/Bottom-up Proteomics. Chemical Reviews 2013, 113 (4) , 2343-2394. https://doi.org/10.1021/cr3003533
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    33. Marina Spivak, Michael S. Bereman, Michael J. MacCoss, and William Stafford Noble . Learning Score Function Parameters for Improved Spectrum Identification in Tandem Mass Spectrometry Experiments. Journal of Proteome Research 2012, 11 (9) , 4499-4508. https://doi.org/10.1021/pr300234m
    34. Marshall W. Bern and Yong J. Kil . Two-Dimensional Target Decoy Strategy for Shotgun Proteomics. Journal of Proteome Research 2011, 10 (12) , 5296-5301. https://doi.org/10.1021/pr200780j
    35. Nitin Gupta, Nuno Bandeira, Uri Keich, Pavel A. Pevzner. Target-Decoy Approach and False Discovery Rate: When Things May Go Wrong. Journal of the American Society for Mass Spectrometry 2011, 22 (7) , 1111-1120. https://doi.org/10.1007/s13361-011-0139-3
    36. Sean McIlwain, Paul Draghicescu, Pragya Singh, David R. Goodlett and William Stafford Noble. Detecting Cross-Linked Peptides by Searching against a Database of Cross-Linked Peptide Pairs. Journal of Proteome Research 2010, 9 (5) , 2488-2495. https://doi.org/10.1021/pr901163d
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    48. Fatema Akter, Sara Bonini, Srigayatri Ponnaiyan, Bianca Kögler-Mohrbacher, Florian Bleibaum, Markus Damme, Bernhard Y. Renard, Dominic Winter. Multi–Cell Line Analysis of Lysosomal Proteomes Reveals Unique Features and Novel Lysosomal Proteins. Molecular & Cellular Proteomics 2023, 22 (3) , 100509. https://doi.org/10.1016/j.mcpro.2023.100509
    49. Charlène Estrada, Liliana Mirabal-Ortega, Laurence Méry, Florent Dingli, Laetitia Besse, Cedric Messaoudi, Damarys Loew, Celio Pouponnot, Corine Bertolotto, Alain Eychène, Sabine Druillennec. MITF activity is regulated by a direct interaction with RAF proteins in melanoma cells. Communications Biology 2022, 5 (1) https://doi.org/10.1038/s42003-022-03049-w
    50. Honglan Li, Seungjin Na, Kyu-Baek Hwang, Eunok Paek. TIDD: tool-independent and data-dependent machine learning for peptide identification. BMC Bioinformatics 2022, 23 (1) https://doi.org/10.1186/s12859-022-04640-y
    51. Derek Wong, Tae Hoon Lee, Amy Lum, Valerie Lan Tao, Stephen Yip. Integrated proteomic analysis of low-grade gliomas reveals contributions of 1p-19q co-deletion to oligodendroglioma. Acta Neuropathologica Communications 2022, 10 (1) https://doi.org/10.1186/s40478-022-01372-1
    52. Yuhua Ji, Zixin Chen, Ziqi Cen, Yuting Ye, Shuyuan Li, Xiaoshuang Lu, Qian Shao, Donghao Wang, Juling Ji, Qiuhong Ji. A comprehensive mouse brain acetylome-the cellular-specific distribution of acetylated brain proteins. Frontiers in Cellular Neuroscience 2022, 16 https://doi.org/10.3389/fncel.2022.980815
    53. Mi Shen, Zixin Chen, Mengru Ming, Zhenghui Cheng, Junjie Sun, Qingyun Liang, Tongxin Shang, Qi Zhang, Songlin Zhou, Yuhua Ji, Fei Ding. The acetylome of adult mouse sciatic nerve. Journal of Neurochemistry 2022, 162 (3) , 262-275. https://doi.org/10.1111/jnc.15648
    54. Bing Wang, Yue Wang, Yu Chen, Mengmeng Gao, Jie Ren, Yueshuai Guo, Chenghao Situ, Yaling Qi, Hui Zhu, Yan Li, Xuejiang Guo. DeepSCP: utilizing deep learning to boost single-cell proteome coverage. Briefings in Bioinformatics 2022, 23 (4) https://doi.org/10.1093/bib/bbac214
    55. Ke Jiang, Anupam Kumar Mondal, Yogita K Adlakha, Jessica Gumerson, Angel Aponte, Linn Gieser, Jung-Woong Kim, Alexis Boleda, Matthew J Brooks, Jacob Nellissery, Donald A Fox, Robert Balaban, Raul Covian, Anand Swaroop. Multiomics analyses reveal early metabolic imbalance and mitochondrial stress in neonatal photoreceptors leading to cell death in Pde6brd1/rd1 mouse model of retinal degeneration. Human Molecular Genetics 2022, 31 (13) , 2137-2154. https://doi.org/10.1093/hmg/ddac013
    56. Heba Badr, Ron Blutrich, Kaitlin Chan, Jiefei Tong, Paul Taylor, Wen Zhang, Ran Kafri, Hannes L. Röst, Ming-Sound Tsao, Michael F. Moran. Proteomic Characterization of a Candidate Polygenic Driver of Metabolism in Non-small Cell Lung Cancer. Journal of Molecular Biology 2022, 434 (13) , 167636. https://doi.org/10.1016/j.jmb.2022.167636
    57. Jiawei Mao, He Zhu, Luyao Liu, Zheng Fang, Mingming Dong, Hongqiang Qin, Mingliang Ye, . MS-Decipher: a user-friendly proteome database search software with an emphasis on deciphering the spectra of O-linked glycopeptides. Bioinformatics 2022, 38 (7) , 1911-1919. https://doi.org/10.1093/bioinformatics/btac014
    58. Martin A. Hoffmann, Louis-Félix Nothias, Marcus Ludwig, Markus Fleischauer, Emily C. Gentry, Michael Witting, Pieter C. Dorrestein, Kai Dührkop, Sebastian Böcker. High-confidence structural annotation of metabolites absent from spectral libraries. Nature Biotechnology 2022, 40 (3) , 411-421. https://doi.org/10.1038/s41587-021-01045-9
    59. Dillon J. Chung, Grey P. Madison, Angel M. Aponte, Komudi Singh, Yuesheng Li, Mehdi Pirooznia, Christopher K. E. Bleck, Nissar A. Darmani, Robert S. Balaban. Metabolic design in a mammalian model of extreme metabolism, the North American least shrew ( Cryptotis parva ). The Journal of Physiology 2022, 600 (3) , 547-567. https://doi.org/10.1113/JP282153
    60. Fahad Saeed, Muhammad Haseeb. Introduction to Mass Spectrometry Data. 2022, 7-19. https://doi.org/10.1007/978-3-031-01960-9_2
    61. Sylvain Lefort, Amal El-Naggar, Susanna Tan, Shane Colborne, Gian Luca Negri, Davide Pellacani, Martin Hirst, Barry Gusterson, Gregg B. Morin, Poul H. Sorensen, Connie J. Eaves. De novo and cell line models of human mammary cell transformation reveal an essential role for Yb-1 in multiple stages of human breast cancer. Cell Death & Differentiation 2022, 29 (1) , 54-64. https://doi.org/10.1038/s41418-021-00836-6
    62. Xinzhou Ge, Yiling Elaine Chen, Dongyuan Song, MeiLu McDermott, Kyla Woyshner, Antigoni Manousopoulou, Ning Wang, Wei Li, Leo D. Wang, Jingyi Jessica Li. Clipper: p-value-free FDR control on high-throughput data from two conditions. Genome Biology 2021, 22 (1) https://doi.org/10.1186/s13059-021-02506-9
    63. Raul Covian, Lanelle Edwards, Yi He, Geumsoo Kim, Carly Houghton, Rodney L. Levine, Robert S. Balaban, . Energy homeostasis is a conserved process: Evidence from Paracoccus denitrificans’ response to acute changes in energy demand. PLOS ONE 2021, 16 (11) , e0259636. https://doi.org/10.1371/journal.pone.0259636
    64. Matt Labenski, Lukas Voortman, Aravind Prasad Medikonda, Philip J. Sherratt, Alan F. Corin. A Chemoproteomics Approach to Determine the Mechanism of Testicular Toxicity for the Bruton’s Tyrosine Kinase Inhibitor CC-292. Journal of Pharmacology and Experimental Therapeutics 2021, 379 (2) , 166-174. https://doi.org/10.1124/jpet.121.000614
    65. Marlene Jensen, Juliane Wippler, Manuel Kleiner, . Evaluation of RNA later as a Field-Compatible Preservation Method for Metaproteomic Analyses of Bacterium-Animal Symbioses. Microbiology Spectrum 2021, 9 (2) https://doi.org/10.1128/Spectrum.01429-21
    66. Audrey Hemadou, Alexandre Fontayne, Jeanny Laroche‐Traineau, Florence Ottones, Philippe Mondon, Stéphane Claverol, Éric Ducasse, Stéphane Sanchez, Sarah Mohamad, Cyril Lorenzato, Martine Duonor‐Cerutti, Gisèle Clofent‐Sanchez, Marie‐Josée Jacobin‐Valat. In Vivo Human Single‐Chain Fragment Variable Phage Display‐Assisted Identification of Galectin‐3 as a New Biomarker of Atherosclerosis. Journal of the American Heart Association 2021, 10 (19) https://doi.org/10.1161/JAHA.120.016287
    67. Shengzhao Xiao, Linhao Li, Jie Yao, Lizhen Wang, Kaimin Li, Chongshi Yang, Chao Wang, Yubo Fan. Microcracks on the Rat Root Surface Induced by Orthodontic Force, Crack Extension Simulation, and Proteomics Study. Annals of Biomedical Engineering 2021, 49 (9) , 2228-2242. https://doi.org/10.1007/s10439-021-02733-y
    68. Shichao Feng, Ryan Sterzenbach, Xuan Guo. Deep learning for peptide identification from metaproteomics datasets. Journal of Proteomics 2021, 247 , 104316. https://doi.org/10.1016/j.jprot.2021.104316
    69. Aubhishek Zaman, Xiaofeng Wu, Andrew Lemoff, Sivaramakrishna Yadavalli, Jeon Lee, Chensu Wang, Jonathan Cooper, Elizabeth A. McMillan, Charles Yeaman, Hamid Mirzaei, Michael A. White, Trever G. Bivona. Exocyst protein subnetworks integrate Hippo and mTOR signaling to promote virus detection and cancer. Cell Reports 2021, 36 (5) , 109491. https://doi.org/10.1016/j.celrep.2021.109491
    70. Anabelle Planques, Vanessa Oliveira Moreira, David Benacom, Clémence Bernard, Laurent Jourdren, Corinne Blugeon, Florent Dingli, Vanessa Masson, Damarys Loew, Alain Prochiantz, Ariel A. Di Nardo. OTX2 Homeoprotein Functions in Adult Choroid Plexus. International Journal of Molecular Sciences 2021, 22 (16) , 8951. https://doi.org/10.3390/ijms22168951
    71. Gaetana Sessa, Belén Gómez‐González, Sonia Silva, Carmen Pérez‐Calero, Romane Beaurepere, Sonia Barroso, Sylvain Martineau, Charlotte Martin, Åsa Ehlén, Juan S Martínez, Bérangère Lombard, Damarys Loew, Stephan Vagner, Andrés Aguilera, Aura Carreira. BRCA2 promotes DNA‐RNA hybrid resolution by DDX5 helicase at DNA breaks to facilitate their repair‡. The EMBO Journal 2021, 40 (7) https://doi.org/10.15252/embj.2020106018
    72. Benjamin C. Orsburn. Proteome Discoverer—A Community Enhanced Data Processing Suite for Protein Informatics. Proteomes 2021, 9 (1) , 15. https://doi.org/10.3390/proteomes9010015
    73. Nikolai Slavov. Single-cell protein analysis by mass spectrometry. Current Opinion in Chemical Biology 2021, 60 , 1-9. https://doi.org/10.1016/j.cbpa.2020.04.018
    74. Richard R. Sprenger, Martin Hermansson, Ditte Neess, Lena Sokol Becciolini, Signe Bek Sørensen, Rolf Fagerberg, Josef Ecker, Gerhard Liebisch, Ole N. Jensen, Dennis E. Vance, Nils J. Færgeman, Robin W. Klemm, Christer S. Ejsing. Lipid molecular timeline profiling reveals diurnal crosstalk between the liver and circulation. Cell Reports 2021, 34 (5) , 108710. https://doi.org/10.1016/j.celrep.2021.108710
    75. Muhammad Usman Tariq, Muhammad Haseeb, Mohammed Aledhari, Rehma Razzak, Reza M. Parizi, Fahad Saeed. Methods for Proteogenomics Data Analysis, Challenges, and Scalability Bottlenecks: A Survey. IEEE Access 2021, 9 , 5497-5516. https://doi.org/10.1109/ACCESS.2020.3047588
    76. Ákos Végvári, Jimmy E. Rodriguez, Roman Zubarev. Single Cell Chemical Proteomics (SCCP) Interrogates the Timing and Heterogeneity of Cancer Cell Commitment to Death. SSRN Electronic Journal 2021, 17 https://doi.org/10.2139/ssrn.3956651
    77. Robert Parker, Arun Tailor, Xu Peng, Annalisa Nicastri, Johannes Zerweck, Ulf Reimer, Holger Wenschuh, Karsten Schnatbaum, Nicola Ternette. The Choice of Search Engine Affects Sequencing Depth and HLA Class I Allele-Specific Peptide Repertoires. Molecular & Cellular Proteomics 2021, 20 , 100124. https://doi.org/10.1016/j.mcpro.2021.100124
    78. Francesca Castoldi, Juliette Humeau, Isabelle Martins, Sylvie Lachkar, Damarys Loew, Florent Dingli, Sylvère Durand, David Enot, Noëlie Bossut, Alexis Chery, Fanny Aprahamian, Yohann Demont, Paule Opolon, Nicolas Signolle, Allan Sauvat, Michaela Semeraro, Lucillia Bezu, Elisa Elena Baracco, Erika Vacchelli, Jonathan G. Pol, Sarah Lévesque, Norma Bloy, Valentina Sica, Maria Chiara Maiuri, Guido Kroemer, Federico Pietrocola. Autophagy-mediated metabolic effects of aspirin. Cell Death Discovery 2020, 6 (1) https://doi.org/10.1038/s41420-020-00365-0
    79. Xijun Liang, Zhonghang Xia, Ling Jian, Yongxiang Wang, Xinnan Niu, Andrew J. Link. A cost-sensitive online learning method for peptide identification. BMC Genomics 2020, 21 (1) https://doi.org/10.1186/s12864-020-6693-y
    80. Michael A. J. Moser, Katherine Sawicka, Jolanta Sawicka, Aleksandra Franczak, Alejandro Cohen, Iwona Bil-Lula, Grzegorz Sawicki. Protection of the transplant kidney during cold perfusion with doxycycline: proteomic analysis in a rat model. Proteome Science 2020, 18 (1) https://doi.org/10.1186/s12953-020-00159-3
    81. Adi Kliot, Richard S Johnson, Michael J MacCoss, Svetlana Kontsedalov, Galina Lebedev, Henryk Czosnek, Michelle Heck, Murad Ghanim. A proteomic approach reveals possible molecular mechanisms and roles for endosymbiotic bacteria in begomovirus transmission by whiteflies. GigaScience 2020, 9 (11) https://doi.org/10.1093/gigascience/giaa124
    82. Dimitry Y. Sorokin, Damon Mosier, Jackie K. Zorz, Xiaoli Dong, Marc Strous. Wenzhouxiangella Strain AB-CW3, a Proteolytic Bacterium From Hypersaline Soda Lakes That Preys on Cells of Gram-Positive Bacteria. Frontiers in Microbiology 2020, 11 https://doi.org/10.3389/fmicb.2020.597686
    83. Jie Wang, Nan Nan, Ning Li, Yutong Liu, Tian-Jing Wang, Inhwan Hwang, Bao Liu, Zheng-Yi Xu. A DNA Methylation Reader–Chaperone Regulator–Transcription Factor Complex Activates OsHKT1;5 Expression during Salinity Stress. The Plant Cell 2020, 32 (11) , 3535-3558. https://doi.org/10.1105/tpc.20.00301
    84. Jesper G. Sørensen, Tommaso Manenti, Jesper S. Bechsgaard, Mads F. Schou, Torsten N. Kristensen, Volker Loeschcke. Pronounced Plastic and Evolutionary Responses to Unpredictable Thermal Fluctuations in Drosophila simulans. Frontiers in Genetics 2020, 11 https://doi.org/10.3389/fgene.2020.555843
    85. Fancheng Yan, Meng Gao, Yiyi Gong, Lin Zhang, Nanping Ai, Jingxue Zhang, Yijie Chai, Shen Wu, Qian Liu, Xian Jiang, Haiteng Deng, Wu Liu. Proteomic analysis of underlying apoptosis mechanisms of human retinal pigment epithelial ARPE‐19 cells in response to mechanical stretch. Journal of Cellular Physiology 2020, 235 (10) , 7604-7619. https://doi.org/10.1002/jcp.29670
    86. Fernando Martínez-Montañés, Albert Casanovas, Richard R. Sprenger, Magdalena Topolska, David L. Marshall, Marta Moreno-Torres, Berwyck L.J. Poad, Stephen J. Blanksby, Martin Hermansson, Ole N. Jensen, Christer S. Ejsing. Phosphoproteomic Analysis across the Yeast Life Cycle Reveals Control of Fatty Acyl Chain Length by Phosphorylation of the Fatty Acid Synthase Complex. Cell Reports 2020, 32 (6) , 108024. https://doi.org/10.1016/j.celrep.2020.108024
    87. Jessica M Bryant, Sebastian Baumgarten, Florent Dingli, Damarys Loew, Ameya Sinha, Aurélie Claës, Peter R Preiser, Peter C Dedon, Artur Scherf. Exploring the virulence gene interactome with CRISPR / dC as9 in the human malaria parasite. Molecular Systems Biology 2020, 16 (8) https://doi.org/10.15252/msb.20209569
    88. Muhammad Tahir, Samina Arshid, Belchor Fontes, Mariana S. Castro, Simone Sidoli, Veit Schwämmle, Isabelle S. Luz, Peter Roepstorff, Wagner Fontes. Phosphoproteomic Analysis of Rat Neutrophils Shows the Effect of Intestinal Ischemia/Reperfusion and Preconditioning on Kinases and Phosphatases. International Journal of Molecular Sciences 2020, 21 (16) , 5799. https://doi.org/10.3390/ijms21165799
    89. Zhengxi Wei, Jinghua Zhao, Jake Niebler, Jian-Jiang Hao, B. Alex Merrick, Menghang Xia. Quantitative Proteomic Profiling of Mitochondrial Toxicants in a Human Cardiomyocyte Cell Line. Frontiers in Genetics 2020, 11 https://doi.org/10.3389/fgene.2020.00719
    90. Michiel L. Bexkens, Renske A. van Gestel, Bas van Breukelen, Rolf T. Urbanus, Jos F. Brouwers, Rienk Nieuwland, Aloysius G.M. Tielens, Jaap J. van Hellemond. Schistosoma mansoni infection affects the proteome and lipidome of circulating extracellular vesicles in the host. Molecular and Biochemical Parasitology 2020, 238 , 111296. https://doi.org/10.1016/j.molbiopara.2020.111296
    91. Lulu Pan, Xijun Wang, Longhai Yang, Lei Zhao, Linhui Zhai, Junyu Xu, Yikun Yang, Yousheng Mao, Shujun Cheng, Ting Xiao, Minjia Tan. Proteomic and Phosphoproteomic Maps of Lung Squamous Cell Carcinoma From Chinese Patients. Frontiers in Oncology 2020, 10 https://doi.org/10.3389/fonc.2020.00963
    92. Li Min, Shengtao Zhu, Rui Wei, Yu Zhao, Si Liu, Peng Li, Shutian Zhang. Integrating SWATH-MS Proteomics and Transcriptome Analysis Identifies CHI3L1 as a Plasma Biomarker for Early Gastric Cancer. Molecular Therapy - Oncolytics 2020, 17 , 257-266. https://doi.org/10.1016/j.omto.2020.03.020
    93. Alan Gerber, Keiichi Ito, Chi-Shuen Chu, Robert G. Roeder. Gene-Specific Control of tRNA Expression by RNA Polymerase II. Molecular Cell 2020, 78 (4) , 765-778.e7. https://doi.org/10.1016/j.molcel.2020.03.023
    94. Johanne Poisson, Marion Tanguy, Hortense Davy, Fatoumata Camara, Marie-Belle El Mdawar, Marouane Kheloufi, Tracy Dagher, Cécile Devue, Juliette Lasselin, Aurélie Plessier, Salma Merchant, Olivier Blanc-Brude, Michèle Souyri, Nathalie Mougenot, Florent Dingli, Damarys Loew, Stephane N. Hatem, Chloé James, Jean-Luc Villeval, Chantal M. Boulanger, Pierre-Emmanuel Rautou. Erythrocyte-derived microvesicles induce arterial spasms in JAK2V617F myeloproliferative neoplasm. Journal of Clinical Investigation 2020, 130 (5) , 2630-2643. https://doi.org/10.1172/JCI124566
    95. Yin-Ze Shi, Kitikiew Suwaree, Yu-Yuan Chen, Chih-Hung Hsu, Jiann-Chu Chen. White shrimp Litopenaeus vannamei hemocytes receiving fucoidan release endogenous molecules that activate and synergize innate immunity in the presence of fucoidan. Aquaculture 2020, 519 , 734720. https://doi.org/10.1016/j.aquaculture.2019.734720
    96. Robert H. Mills, Jacob M. Wozniak, Alison Vrbanac, Anaamika Campeau, Benoit Chassaing, Andrew Gewirtz, Rob Knight, David J. Gonzalez. Organ-level protein networks as a reference for the host effects of the microbiome. Genome Research 2020, 30 (2) , 276-286. https://doi.org/10.1101/gr.256875.119
    97. Rune Matthiesen. Solution to Dark Matter Identified by Mass-Tolerant Database Search. 2020, 231-240. https://doi.org/10.1007/978-1-4939-9744-2_9
    98. A. Laboulais, S. Malmström, C. Dejean, M. Cardoso, T. Le Meur, L. Almeida, C. Goze-Bac, S. Pucheu. New Automatic and Robust Measures to Evaluate Hearing Loss and Tinnitus in Preclinical Models. 2020, 159-186. https://doi.org/10.1007/978-3-030-40413-0_7
    99. Igor H. Wierzbicki, Anaamika Campeau, Diana Dehaini, Maya Holay, Xiaoli Wei, Trever Greene, Man Ying, Jenna S. Sands, Anne Lamsa, Elina Zuniga, Kit Pogliano, Ronnie H. Fang, Christopher N. LaRock, Liangfang Zhang, David J. Gonzalez. Group A Streptococcal S Protein Utilizes Red Blood Cells as Immune Camouflage and Is a Critical Determinant for Immune Evasion. Cell Reports 2019, 29 (10) , 2979-2989.e15. https://doi.org/10.1016/j.celrep.2019.11.001
    100. Nathan Egge, Sonja L.B. Arneaud, Pauline Wales, Melina Mihelakis, Jacob McClendon, Rene Solano Fonseca, Charles Savelle, Ian Gonzalez, Atossa Ghorashi, Sivaramakrishna Yadavalli, William J. Lehman, Hamid Mirzaei, Peter M. Douglas. Age-Onset Phosphorylation of a Minor Actin Variant Promotes Intestinal Barrier Dysfunction. Developmental Cell 2019, 51 (5) , 587-601.e7. https://doi.org/10.1016/j.devcel.2019.11.001
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