Bioinformatics Methods for Mass Spectrometry-Based Proteomics Data Analysis

STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets

Szklarczyk, D., Gable, A. L., Lyon, D., Junge, A., Wyder, S., Huerta-Cepas, J., Simonovic, M., Doncheva, N. T., Morris, J. H., Bork, P., et al. (2019) · Nucleic Acids Research · doi:10.1093/nar/gky1131 · Cited by 17,749 · see citing works

DAVID: Database for Annotation, Visualization, and Integrated Discovery

Dennis, G., Sherman, B. T., Hosack, D. A., Yang, J., Gao, W., Lane, H. C., & Lempicki, R. A. (2003) · Genome Biology · doi:10.1186/gb-2003-4-5-p3 · Cited by 9,327 · see citing works

KEGG: new perspectives on genomes, pathways, diseases and drugs

Kanehisa, M., Furumichi, M., Tanabe, M., Sato, Y., & Morishima, K. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkw1092 · Cited by 8,865 · see citing works

The STRING database in 2017: quality-controlled protein–protein association networks, made broadly accessible

Szklarczyk, D., Morris, J. H., Cook, H., Kuhn, M., Wyder, S., Simonovic, M., Santos, A., Doncheva, N. T., Roth, A., Bork, P., et al. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkw937 · Cited by 6,980 · see citing works

An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database

Eng, J. K., McCormack, A. L., & Yates, J. R. (1994) · Journal of the American Society for Mass Spectrometry · doi:10.1016/1044-0305(94)80016-2 · Cited by 6,484 · see citing works

Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics

Ong, S.-E., Blagoev, B., Kratchmarova, I., Kristensen, D. B., Steen, H., Pandey, A., & Mann, M. (2002) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m200025-mcp200 · Cited by 5,574 · see citing works

Andromeda: A Peptide Search Engine Integrated into the MaxQuant Environment

Cox, J., Neuhauser, N., Michalski, A., Scheltema, R. A., Olsen, J. V., & Mann, M. (2011) · Journal of Proteome Research · doi:10.1021/pr101065j · Cited by 5,349 · see citing works

Accurate proteome-wide label-free quantification by delayed normalization and maximal peptide ratio extraction, termed MaxLFQ

Cox, J., Hein, M. Y., Luber, C. A., Paron, I., Nagaraj, N., & Mann, M. (2014) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m113.031591 · Cited by 5,180 · see citing works

A statistical model for identifying proteins by tandem mass spectrometry.

Nesvizhskii, A., Keller, A., Kolker, E., & Aebersold, R. (2003) · Analytical Chemistry · doi:10.1021/ac0341261 · Cited by 4,902 · see citing works

Skyline: an open source document editor for creating and analyzing targeted proteomics experiments

MacLean, B., Tomazela, D. M., Shulman, N., Chambers, M., Finney, G. L., Frewen, B., Kern, R., Tabb, D. L., Liebler, D. C., & MacCoss, M. J. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq054 · Cited by 4,697 · see citing works

The MaxQuant computational platform for mass spectrometry-based shotgun proteomics

Tyanova, S., Temu, T., & Cox, J. (2016) · Nature Protocols · doi:10.1038/nprot.2016.136 · Cited by 4,691 · see citing works

Quantitative analysis of complex protein mixtures using isotope-coded affinity tags

Gygi, S. P., Rist, B., Gerber, S. A., Turecek, F., Gelb, M. H., & Aebersold, R. (1999) · Nature Biotechnology · doi:10.1038/13690 · Cited by 4,683 · cited 1× · see citing works

The Gene Ontology (GO) database and informatics resource

Gene Ontology Consortium (2003) · Nucleic Acids Research · doi:10.1093/nar/gkh036 · Cited by 4,533 · see citing works

Target-decoy search strategy for increased confidence in large-scale protein identifications by mass spectrometry

Elias, J. E., & Gygi, S. P. (2007) · Nature Methods · doi:10.1038/nmeth1019 · Cited by 3,925 · see citing works

Correlation between Protein and mRNA Abundance in Yeast

Gygi, S. P., Rochon, Y., Franza, B. R., & Aebersold, R. (1999) · Molecular and Cellular Biology · doi:10.1128/mcb.19.3.1720 · Cited by 3,819 · see citing works

TANDEM: matching proteins with tandem mass spectra

Craig, R., & Beavis, R. C. (2004) · Bioinformatics · doi:10.1093/bioinformatics/bth092 · Cited by 2,553 · see citing works

Variance stabilization applied to microarray data calibration and to the quantification of differential expression

Huber, W., von Heydebreck, A., Sültmann, H., Poustka, A., & Vingron, M. (2002) · Bioinformatics · doi:10.1093/bioinformatics/18.suppl_1.s96 · Cited by 2,440 · see citing works

DAVID: Database for Annotation, Visualization, and Integrated Discovery

Dennis, G., Sherman, B. T., Hosack, D. A., Yang, J., Gao, W., Lane, H. C., & Lempicki, R. A. (2003) · Genome biology · doi:10.1186/gb-2003-4-9-r60 · Cited by 2,383 · see citing works

Pathview: an R/Bioconductor package for pathway-based data integration and visualization

Luo, W., & Brouwer, C. (2013) · Bioinformatics · doi:10.1093/bioinformatics/btt285 · Cited by 2,297 · see citing works

Exponentially Modified Protein Abundance Index (emPAI) for Estimation of Absolute Protein Amount in Proteomics by the Number of Sequenced Peptides per Protein

Ishihama, Y., Oda, Y., Tabata, T., Sato, T., Nagasu, T., Rappsilber, J., & Mann, M. (2005) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m500061-mcp200 · Cited by 2,055 · see citing works

AmiGO: online access to ontology and annotation data

Carbon, S., Ireland, A., Mungall, C., Shu, S., Marshall, B., Lewis, S., Hub, T. A., & the Web Presence Working Group (2008) · Bioinformatics · doi:10.1093/bioinformatics/btn615 · Cited by 1,918 · see citing works

Mass-spectrometry-based draft of the human proteome

Wilhelm, M., Schlegl, J., Hahne, H., Gholami, A. M., Lieberenz, M., Savitski, M. M., Ziegler, E., Butzmann, L., Gessulat, S., Marx, H., et al. (2014) · Nature · doi:10.1038/nature13319 · Cited by 1,820 · see citing works

Reactome: a database of reactions, pathways and biological processes

Croft, D., O'Kelly, G., Wu, G., Haw, R., Gillespie, M., Matthews, L., Caudy, M., Garapati, P., Gopinath, G., Jassal, B., et al. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkq1018 · Cited by 1,751 · see citing works

PhosphoSitePlus: a comprehensive resource for investigating the structure and function of experimentally determined post-translational modifications in man and mouse

Hornbeck, P. V., Kornhauser, J. M., Tkachev, S., Zhang, B., Skrzypek, E., Murray, B. W., Latham, V. M., & Sullivan, M. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkr1122 · Cited by 1,636 · see citing works

Absolute Quantification of Proteins by LCMSE

Silva, J. C., Gorenstein, M. V., Li, G.-Z., Vissers, J. P. C., & Geromanos, S. J. (2006) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m500230-mcp200 · Cited by 1,529 · see citing works

Open Mass Spectrometry Search Algorithm

Geer, L. Y., Markey, S. P., Kowalak, J. A., Wagner, L., Xu, M. Q., Maynard, D., Yang, X., Shi, W., & Bryant, S. H. (2004) · Journal of Proteome Research · doi:10.1021/pr0499491 · Cited by 1,420 · see citing works

PEAKS: powerful software for peptide de novo sequencing by tandem mass spectrometry

Ma, B., Zhang, K., Hendrie, C., Liang, C., Li, M., Doherty‐Kirby, A., & Lajoie, G. (2003) · Rapid Communications in Mass Spectrometry · doi:10.1002/rcm.1196 · Cited by 1,382 · see citing works

A comparison of selected mRNA and protein abundances in human liver

Anderson, L., & Seilhamer, J. (1997) · Electrophoresis · doi:10.1002/elps.1150180333 · Cited by 1,266 · see citing works

Pathway Commons, a web resource for biological pathway data

Cerami, E. G., Gross, B. E., Demir, E., Rodchenkov, I., Babur, O., Anwar, N., Schultz, N., Bader, G. D., & Sander, C. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkq1039 · Cited by 1,101 · see citing works

PEAKS DB: De Novo Sequencing Assisted Database Search for Sensitive and Accurate Peptide Identification

Zhang, J., Xin, L., Shan, B., Chen, W., Xie, M., Yuen, D., Zhang, W., Zhang, Z., Lajoie, G., & Ma, B. (2011) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m111.010587 · Cited by 1,073 · see citing works

Accurate quantitation of protein expression and site-specific phosphorylation.

Oda, Y., Huang, K., Cross, F., Cowburn, D., & Chait, B. (1999) · Proceedings of the National Academy of Sciences of the United States of America · doi:10.1073/pnas.96.12.6591 · Cited by 1,011 · see citing works

Quantitative profiling of differentiation-induced microsomal proteins using isotope-coded affinity tags and mass spectrometry

Han, D. K. M., Eng, J. K., Zhou, H., & Aebersold, R. H. (2001) · Nature Biotechnology · doi:10.1038/nbt1001-946 · Cited by 868 · see citing works

Continuous Distributed Representation of Biological Sequences for Deep Proteomics and Genomics

Asgari, E., & Mofrad, M. R. K. (2015) · PLoS ONE · doi:10.1371/journal.pone.0141287 · Cited by 817 · see citing works

Protein labeling by iTRAQ: A new tool for quantitative mass spectrometry in proteome research

Wiese, S., Reidegeld, K. A., Meyer, H. E., & Warscheid, B. (2006) · PROTEOMICS · doi:10.1002/pmic.200600422 · Cited by 803 · see citing works

Proteogenomics: concepts, applications and computational strategies

Nesvizhskii, A. I. (2014) · Nature Methods · doi:10.1038/nmeth.3144 · Cited by 763 · see citing works

PANTHER Pathway: An Ontology-Based Pathway Database Coupled with Data Analysis Tools

Mi, H., & Thomas, P. D. (2009) · Methods in molecular biology · doi:10.1007/978-1-60761-175-2_7 · Cited by 750 · see citing works

A guided tour of the Trans‐Proteomic Pipeline

Deutsch, E. W., Mendoza, L., Shteynberg, D. D., Farrah, T., Lam, H., Tasman, N., Sun, Z., Nilsson, E. J., Pratt, B. S., Prazen, B. J., et al. (2010) · PROTEOMICS · doi:10.1002/pmic.200900375 · Cited by 746 · see citing works

Missing Value Imputation Approach for Mass Spectrometry-based Metabolomics Data

Wei, R., Wang, J., Su, M., Jia, E., Chen, S., Chen, T., & Ni, Y. (2018) · Scientific Reports · doi:10.1038/s41598-017-19120-0 · Cited by 720 · see citing works

Computational prediction of proteotypic peptides for quantitative proteomics

Mallick, P., Schirle, M., Chen, S. S., Flory, M. R., Lee, H., Martin, D. B., Ranish, J. A., Raught, B., Schmitt, R., Werner, T., et al. (2006) · Nature Biotechnology · doi:10.1038/nbt1275 · Cited by 695 · see citing works

The future of biocuration

Howe, D. G., Costanzo, M. C., Fey, P., Gojobori, T., Hannick, L. I., Hide, W., Hill, D. P., Kania, R., Schaeffer, M. L., Pierre, S. S., et al. (2008) · Nature · doi:10.1038/455047a · Cited by 695 · see citing works

PepNovo: De Novo Peptide Sequencing via Probabilistic Network Modeling

Frank, A. M., & Pevzner, P. A. (2005) · Analytical Chemistry · doi:10.1021/ac048788h · Cited by 691 · see citing works

A “Proteomic Ruler” for Protein Copy Number and Concentration Estimation without Spike-in Standards

Wiśniewski, J. R., Hein, M. Y., Cox, J., & Mann, M. (2014) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m113.037309 · Cited by 690 · see citing works

Systems biology properties of reconstructed networks

Palsson, B. Ø. (2006) · Cited by 684 · see citing works

Byonic: Advanced Peptide and Protein Identification Software

Bern, M., Kil, Y. J., & Becker, C. (2012) · Current Protocols in Bioinformatics · doi:10.1002/0471250953.bi1320s40 · Cited by 659 · see citing works

OpenMS – An open-source software framework for mass spectrometry

Sturm, M., Bertsch, A., Gröpl, C., Hildebrandt, A., Hussong, R., Lange, E., Pfeifer, N., Schulz-Trieglaff, O. B., Zerck, A., Reinert, K., et al. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-163 · Cited by 646 · see citing works

Target-Decoy Search Strategy for Mass Spectrometry-Based Proteomics

Elias, J. E., & Gygi, S. P. (2010) · Methods in Molecular Biology · doi:10.1007/978-1-60761-444-9_5 · Cited by 644 · see citing works

DIA-Umpire: comprehensive computational framework for data-independent acquisition proteomics

Tsou, C., Avtonomov, D. M., Larsen, B. G., Tucholska, M., Choi, H., Gingras, A., & Nesvizhskii, A. I. (2015) · Nature Methods · doi:10.1038/nmeth.3255 · Cited by 622 · see citing works

Systems Biology: Properties of Reconstructed Networks

Palsson, B. Ø. (2006) · doi:10.1017/cbo9780511790515 · Cited by 617 · see citing works

Isobaric Labeling-Based Relative Quantification in Shotgun Proteomics

Rauniyar, N., & Yates, J. R. (2014) · Journal of Proteome Research · doi:10.1021/pr500880b · Cited by 597 · see citing works

Global, quantitative and dynamic mapping of protein subcellular localization

Itzhak, D. N., Tyanova, S., Cox, J., & Borner, G. H. H. (2016) · eLife · doi:10.7554/elife.16950 · Cited by 595 · see citing works

De Novo Peptide Sequencing via Tandem Mass Spectrometry

Dančík, V., Addona, T. A., Clauser, K. R., Vath, J. E., & Pevzner, P. A. (1999) · Journal of Computational Biology · doi:10.1089/106652799318300 · Cited by 593 · see citing works

Progress in Top-Down Proteomics and the Analysis of Proteoforms

Toby, T. K., Fornelli, L., & Kelleher, N. L. (2016) · Annual Review of Analytical Chemistry · doi:10.1146/annurev-anchem-071015-041550 · Cited by 576 · see citing works

InsPecT: Identification of Posttranslationally Modified Peptides from Tandem Mass Spectra

Tanner, S. W., Shu, H., Frank, A. M., Wang, L.-C., Zandi, E., Mumby, M. C., Pevzner, P. A., & Bafna, V. (2005) · Analytical Chemistry · doi:10.1021/ac050102d · Cited by 568 · see citing works

Multiple comparison analysis testing in ANOVA

McHugh, M. L. (2011) · Biochemia Medica · doi:10.11613/bm.2011.029 · Cited by 532 · see citing works

HIPPIE v2.0: enhancing meaningfulness and reliability of protein–protein interaction networks

Alanis‐Lobato, G., Andrade-Navarro, M. A., & Schaefer, M. H. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw985 · Cited by 520 · see citing works

A novel strategy for quantitative proteomics using isotope‐coded protein labels

Schmidt, A., Kellermann, J., & Lottspeich, F. (2004) · PROTEOMICS · doi:10.1002/pmic.200400873 · Cited by 507 · see citing works

The Supervised Learning No-Free-Lunch Theorems

Wolpert, D. H. (2002) · Springer eBooks · doi:10.1007/978-1-4471-0123-9_3 · Cited by 476 · see citing works

De novo peptide sequencing by deep learning

Tran, N. H., Zhang, X., Xin, L., Shan, B., & Li, M. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1705691114 · Cited by 437 · see citing works

Sequence database searches viade novo peptide sequencing by tandem mass spectrometry

Taylor, J. A., & Johnson, R. S. (1997) · Rapid Communications in Mass Spectrometry · doi:10.1002/(sici)1097-0231(19970615)11:9 · Cited by 415 · see citing works

TMT Labeling for the Masses: A Robust and Cost-efficient, In-solution Labeling Approach

Zecha, J., Satpathy, S., Kanashova, T., Avanessian, S. C., Kane, M. H., Clauser, K. R., Mertins, P., Carr, S. A., & Küster, B. (2019) · Molecular & Cellular Proteomics · doi:10.1074/mcp.tir119.001385 · Cited by 403 · see citing works

In-Vivo Quantitative Proteomics Reveals a Key Contribution of Post-Transcriptional Mechanisms to the Circadian Regulation of Liver Metabolism

Robles, M. S., Cox, J., & Mann, M. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004047 · Cited by 383 · see citing works

Best practices and benchmarks for intact protein analysis for top-down mass spectrometry

Donnelly, D. P., Rawlins, C. M., DeHart, C. J., Fornelli, L., Schachner, L. F., Lin, Z., Lippens, J. L., Aluri, K. C., Sarin, R., Chen, B., et al. (2019) · Nature Methods · doi:10.1038/s41592-019-0457-0 · Cited by 377 · see citing works

Deep learning enables de novo peptide sequencing from data-independent-acquisition mass spectrometry

Tran, N. H., Qiao, R., Xin, L., Chen, X., Liu, C., Zhang, X., Shan, B., Ghodsi, A., & Li, M. (2018) · Nature Methods · doi:10.1038/s41592-018-0260-3 · Cited by 375 · see citing works

A systematic evaluation of normalization methods in quantitative label-free proteomics

Välikangas, T., Suomi, T., & Elo, L. L. (2016) · Briefings in Bioinformatics · doi:10.1093/bib/bbw095 · Cited by 336 · see citing works

Proteomic maps of breast cancer subtypes

Tyanova, S., Albrechtsen, R., Kronqvist, P., Cox, J., Mann, M., & Geiger, T. (2016) · Nature Communications · doi:10.1038/ncomms10259 · Cited by 327 · see citing works

Mass Spectrometry Applied to Bottom-Up Proteomics: Entering the High-Throughput Era for Hypothesis Testing

Gillet, L. C., Leitner, A., & Aebersold, R. (2016) · Annual Review of Analytical Chemistry · doi:10.1146/annurev-anchem-071015-041535 · Cited by 323 · see citing works

The KSEA App: a web-based tool for kinase activity inference from quantitative phosphoproteomics

Wiredja, D. D., Koyutürk, M., & Chance, M. R. (2017) · Bioinformatics · doi:10.1093/bioinformatics/btx415 · Cited by 319 · see citing works

Detecting significant changes in protein abundance

Kammers, K., Cole, R. N., Tiengwe, C., & Ruczinski, I. (2015) · EuPA Open Proteomics · doi:10.1016/j.euprot.2015.02.002 · Cited by 314 · see citing works

Protein Identification False Discovery Rates for Very Large Proteomics Data Sets Generated by Tandem Mass Spectrometry

Reiter, L., Claassen, M., Schrimpf, S. P., Jovanovic, M., Schmidt, A., Buhmann, J. M., Hengartner, M. O., & Aebersold, R. (2009) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m900317-mcp200 · Cited by 312 · see citing works

A Review on Quantitative Multiplexed Proteomics

Pappireddi, N., Martin, L., & Wühr, M. (2019) · ChemBioChem · doi:10.1002/cbic.201800650 · Cited by 299 · see citing works

Review, evaluation, and discussion of the challenges of missing value imputation for mass spectrometry-based label-free global proteomics

Webb-Robertson, B.-J. M., Wiberg, H. K., Matzke, M. M., Brown, J. N., Wang, J., McDermott, J. E., Smith, R. D., Rodland, K. D., Metz, T. O., Pounds, J. G., et al. (2015) · Journal of Proteome Research · doi:10.1021/pr501138h · Cited by 294 · see citing works

i-Tracker: For quantitative proteomics using iTRAQ™

Shadforth, I., Dunkley, T. P. J., Lilley, K. S., & Bessant, C. (2005) · BMC Genomics · doi:10.1186/1471-2164-6-145 · Cited by 281 · see citing works

Use of stable isotope labeling by amino acids in cell culture as a spike-in standard in quantitative proteomics

Geiger, T., Wiśniewski, J. R., Cox, J., Zanivan, S. R., Krüger, M., Ishihama, Y., & Mann, M. (2011) · Nature Protocols · doi:10.1038/nprot.2010.192 · Cited by 277 · see citing works

TopPIC: a software tool for top-down mass spectrometry-based proteoform identification and characterization

Kou, Q., Xun, L., & Liu, X. (2016) · Bioinformatics · doi:10.1093/bioinformatics/btw398 · Cited by 276 · see citing works

Identification of diagnostic markers for tuberculosis by proteomic fingerprinting of serum

Agranoff, D., Fernández-Reyes, D., Papadopoulos, M. C., Rojas, S. A., Herbster, M., Loosemore, A., Tarelli, E., Sheldon, J., Schwenk, A., Pollok, R., et al. (2006) · The Lancet · doi:10.1016/s0140-6736(06)69342-2 · Cited by 263 · see citing works

An integrated workflow for charting the human interaction proteome: insights into the PP2A system

Glatter, T., Wepf, A., Aebersold, R. H., & Gstaiger, M. (2009) · Molecular Systems Biology · doi:10.1038/msb.2008.75 · Cited by 259 · see citing works

Multiplexed and data‐independent tandem mass spectrometry for global proteome profiling

Chapman, J. D., Goodlett, D. R., & Masselon, C. (2013) · Mass Spectrometry Reviews · doi:10.1002/mas.21400 · Cited by 258 · see citing works

Enhanced Global Post-translational Modification Discovery with MetaMorpheus

Solntsev, S. K., Shortreed, M. R., Frey, B. L., & Smith, L. M. (2018) · Journal of Proteome Research · doi:10.1021/acs.jproteome.7b00873 · Cited by 258 · see citing works

MSQuant, an Open Source Platform for Mass Spectrometry-Based Quantitative Proteomics

Mortensen, P., Gouw, J. W., Olsen, J. V., Ong, S., Rigbolt, K. T. G., Bunkenborg, J., Cox, J., Foster, L. J., Heck, A. J. R., Blagoev, B., et al. (2009) · Journal of Proteome Research · doi:10.1021/pr900721e · Cited by 254 · see citing works

Generating high quality libraries for DIA MS with empirically corrected peptide predictions

Searle, B. C., Swearingen, K. E., Barnes, C. A., Schmidt, T., Gessulat, S., Küster, B., & Wilhelm, M. (2020) · Nature Communications · doi:10.1038/s41467-020-15346-1 · Cited by 251 · see citing works

A Fast SEQUEST Cross Correlation Algorithm

Eng, J. K., Fischer, B., Grossmann, J., & MacCoss, M. J. (2008) · Journal of Proteome Research · doi:10.1021/pr800420s · Cited by 244 · see citing works

SIGNOR: a database of causal relationships between biological entities

Perfetto, L., Briganti, L., Calderone, A., Perpetuini, A. C., Iannuccelli, M., Langone, F., Licata, L., Marinkovic, M., Mattioni, A., Pavlidou, T., et al. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv1048 · Cited by 235 · see citing works

Affinity purification‐mass spectrometry

Bauer, A., & Küster, B. (2003) · European Journal of Biochemistry · doi:10.1046/j.1432-1033.2003.03428.x · Cited by 232 · see citing works

Inferring causal molecular networks: empirical assessment through a community-based effort

Hill, S. M., Heiser, L. M., Cokelaer, T., Unger, M., Nesser, N. K., Carlin, D. E., Zhang, Y., Sokolov, A., Paull, E., Wong, C., et al. (2016) · Nature Methods · doi:10.1038/nmeth.3773 · Cited by 232 · see citing works

Tools for Label-free Peptide Quantification

Nahnsen, S., Bielow, C., Reinert, K., & Kohlbacher, O. (2012) · Molecular & Cellular Proteomics · doi:10.1074/mcp.r112.025163 · Cited by 223 · see citing works

False Discovery Rates and Related Statistical Concepts in Mass Spectrometry-Based Proteomics

Choi, H., & Nesvizhskii, A. I. (2007) · Journal of Proteome Research · doi:10.1021/pr700747q · Cited by 217 · see citing works

Spatial Segmentation of Imaging Mass Spectrometry Data with Edge-Preserving Image Denoising and Clustering

Alexandrov, T., Becker, M. S., Deininger, S., Ernst, G., Wehder, L., Grasmair, M., von Eggeling, F., Thiele, H., & Maaß, P. (2010) · Journal of Proteome Research · doi:10.1021/pr100734z · Cited by 213 · see citing works

A Heuristic Method for Assigning a False-discovery Rate for Protein Identifications from Mascot Database Search Results

Weatherly, D. B., Atwood, J., Minning, T. A., Cavola, C., Tarleton, R. L., & Orlando, R. (2005) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m400215-mcp200 · Cited by 210 · see citing works

Functional modules by relating protein interaction networks and gene expression

Tornow, S. (2003) · Nucleic Acids Research · doi:10.1093/nar/gkg838 · Cited by 195 · see citing works

JUMP: a tag-based database search tool for peptide identification with high sensitivity and accuracy

Wang, X., Li, Y., Wu, Z., Wang, H., Tan, H., & Peng, J. (2014) · Molecular & Cellular Proteomics · doi:10.1074/mcp.o114.039586 · Cited by 194 · see citing works

Precision Oncology beyond Targeted Therapy: Combining Omics Data with Machine Learning Matches the Majority of Cancer Cells to Effective Therapeutics

Ding, M. Q., Chen, L., Cooper, G. F., Young, J. D., & Lu, X. (2017) · Molecular Cancer Research · doi:10.1158/1541-7786.mcr-17-0378 · Cited by 191 · see citing works

NovoHMM: A Hidden Markov Model for de Novo Peptide Sequencing

Fischer, B., Röth, V., Roos, F. F., Grossmann, J., Baginsky, S., Widmayer, P., Gruissem, W., & Buhmann, J. M. (2005) · Analytical Chemistry · doi:10.1021/ac0508853 · Cited by 191 · see citing works

VIPER: an advanced software package to support high-throughput LC-MS peptide identification

Monroe, M. E., Tolić, N., Jaitly, N., Shaw, J. L., Adkins, J., & Smith, R. D. (2007) · Bioinformatics · doi:10.1093/bioinformatics/btm281 · Cited by 189 · see citing works

ModifiComb, a New Proteomic Tool for Mapping Substoichiometric Post-translational Modifications, Finding Novel Types of Modifications, and Fingerprinting Complex Protein Mixtures

Savitski, M. M., Nielsen, M. L., & Zubarev, R. A. (2006) · Molecular & Cellular Proteomics · doi:10.1074/mcp.t500034-mcp200 · Cited by 188 · see citing works

Significance, P values and t-tests

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PECAN: library-free peptide detection for data-independent acquisition tandem mass spectrometry data

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Impact of High Salt Diet on Cerebral Vascular Function and Stroke in Tff3−/−/C57BL/6N Knockout and WT (C57BL/6N) Control Mice

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A new estimation of protein-level false discovery rate

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A novel strategy using MASCOT Distiller for analysis of cleavable isotope‐coded affinity tag data to quantify protein changes in plasma

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Focus on the 20-Year Anniversary of SEQUEST

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Cancer proteogenomics: current impact and future prospects

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Mass spectrometry-based proteomics as an emerging tool in clinical laboratories

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Modern venomics—Current insights, novel methods, and future perspectives in biological and applied animal venom research

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Proteomes Are of Proteoforms: Embracing the Complexity

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Deep learning–driven multi-omics analysis: enhancing cancer diagnostics and therapeutics

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Omics approaches for the assessment of biological responses to nanoparticles

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AlphaPept: a modern and open framework for MS-based proteomics

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Decrypting proteomics, transcriptomics, genomics, and integrated omics for augmenting the abiotic, biotic, and climate change stress resilience in plants

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Characteristics of Food Protein-Derived Antidiabetic Bioactive Peptides: A Literature Update

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Understanding Cervical Cancer through Proteomics

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The Omnitrap Platform: A Versatile Segmented Linear Ion Trap for Multidimensional Multiple-Stage Tandem Mass Spectrometry

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Recent Findings on the Isolation, Identification and Quantification of Bioactive Peptides

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Quantitative mass spectrometry imaging: therapeutics & biomolecules

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Application of Machine Learning in Spatial Proteomics

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Identification of cross-talk pathways and ferroptosis-related genes in periodontitis and type 2 diabetes mellitus by bioinformatics analysis and experimental validation

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Unbiasedly decoding the tumor microenvironment with single-cell multiomics analysis in pancreatic cancer

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How to use open-pFind in deep proteomics data analysis?— A protocol for rigorous identification and quantitation of peptides and proteins from mass spectrometry data

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Using Artificial Intelligence to Better Predict and Develop Biomarkers

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Proteomics of the heart

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Recent advances in mass-spectrometry based proteomics software, tools and databases

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Proteomics as a tool to disclose the cellular and molecular mechanisms of selected anticancer gold compounds

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Molecular Proteomics and Signalling of Human Platelets in Health and Disease

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Label-free visual proteomics: Coupling MS- and EM-based approaches in structural biology

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Illuminating the oral microbiome and its host interactions: recent advancements in omics and bioinformatics technologies in the context of oral microbiome research

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Proteomics and plant biology: contributions to date and a look towards the next decade

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Review of Liquid Chromatography-Mass Spectrometry-Based Proteomic Analyses of Body Fluids to Diagnose Infectious Diseases

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Towards Building a Quantitative Proteomics Toolbox in Precision Medicine: A Mini-Review

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Metaproteomics insights into fermented fish and vegetable products and associated microbes

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Mass Spectrometry Strategies for O-Glycoproteomics

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DNA-Based Data Storage Systems: A Review of Implementations and Code Constructions

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MS Amanda 2.0: Advancements in the standalone implementation

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Plant responses to plant growth promoting bacteria: Insights from proteomics

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Omics applications in the fight against abuse of anabolic substances in cattle: challenges, perspectives and opportunities

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Harnessing Multi-Omics Strategies and Bioinformatics Innovations for Advancing Soybean Improvement: A Comprehensive Review

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Mass spectrometry methods for analysis of extracellular matrix components in neurological diseases

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DMT-EV: An Explainable Deep Network for Dimension Reduction

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Metabolomics and Proteomics in Prostate Cancer Research: Overview, Analytical Techniques, Data Analysis, and Recent Clinical Applications

Al-Daffaie, F. M., Al-Mudhafar, S. F., Alhomsi, A., Tarazi, H., Almehdi, A. M., El‐Huneidi, W., Abu‐Gharbieh, E., Bustanji, Y. K., Alqudah, M. A. Y., Abuhelwa, A. Y., et al. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms25105071 · Cited by 23 · see citing works

Molecular Pathways Involved in Frontotemporal Lobar Degeneration with TDP-43 Proteinopathy: What Can We Learn from Proteomics?

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OmicScope unravels systems-level insights from quantitative proteomics data

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Bioinformatic Analysis of Temporal and Spatial Proteome Alternations During Infections

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FN1 Promotes Thyroid Carcinoma Cell Proliferation and Metastasis by Activating the NF-Κb Pathway

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Integrated Proteomics and Metabolomics Link Acne to the Action Mechanisms of Cryptotanshinone Intervention

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Developing mass spectrometry for the quantitative analysis of neuropeptides

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Aptamer-Functionalized Interface Nanopores Enable Amino Acid-Specific Peptide Detection

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Comparative database search engine analysis on massive tandem mass spectra of pork-based food products for halal proteomics

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Proteomics techniques in protein biomarker discovery

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Mass Spectrometry–Based Proteomics in Clinical Diagnosis of Amyloidosis and Multiple Myeloma: A Review (2012–2024)

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Proteomics as a tool to improve novel insights into skin diseases: what we know and where we should be going

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From protein biomarkers to proteomics in dementia with Lewy Bodies

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Bringing synapses into focus: Recent advances in synaptic imaging and mass-spectrometry for studying synaptopathy

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Integration of proteomics in the molecular tumor board

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Label-free plasma proteomics for the identification of the putative biomarkers of oral squamous cell carcinoma

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Spermatozoa and seminal plasma proteomics: Too many molecules, too few markers. The case of bovine and porcine semen

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Advances in Proteomics Allow Insights Into Neuronal Proteomes

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Normative Data on Serum and Plasma Tryptophan and Kynurenine Concentrations from 8089 Individuals Across 120 Studies: A Systematic Review and Meta-Analysis

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Exosomal Proteomics: Unveiling Novel Insights into Lung Cancer

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Multi-omics tools for understanding Trichoderma-plant symbiosis: biotechnological developments and future directions

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The top 100 most cited articles on rhabdomyolysis: A bibliometric analysis

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Applications of Proteomic Tools to Study Insect Vector–Plant Virus Interactions

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Web of venom: exploration of big data resources in animal toxin research

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From Affinity to Proximity Techniques to Investigate Protein Complexes in Plants

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A survey of the European Open Science Cloud services for expanding the capacity and capabilities of multidisciplinary scientific applications

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The Emerging Role of Omics-Based Approaches in Plant Virology

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Mass Spectrometry Measurements of Neuropeptides: From Identification to Quantitation

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Proteomic Analyses of Vitreous in Proliferative Diabetic Retinopathy: Prior Studies and Future Outlook

Weber, S. R., Zhao, Y., Gates, C., Ma, J., Leprevost, F. D. V., Basrur, V., Nesvizhskii, A. I., Gardner, T. W., & Sundstrom, J. M. (2021) · Journal of Clinical Medicine · doi:10.3390/jcm10112309 · Cited by 14 · see citing works

Inferring early-life host and microbiome functions by mass spectrometry-based metaproteomics and metabolomics

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Current applications and challenges of artificial intelligence in pathology

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Proteomics in biomarker discovery: uncovering disease-specific interactome and post-translational modification networks

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Prognostic Biomarkers Based on Proteomic Technology in COPD: A Recent Review

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Integration of metabolomics and proteomics analysis to explore the mechanism of neurotoxicity induced by receipt of isoniazid and rifampicin in mice

Qu, X., Ma, J., Gao, H., Zhang, Y., Zhai, J., Gong, J., Song, Y., & Hu, T. (2022) · NeuroToxicology · doi:10.1016/j.neuro.2022.11.004 · Cited by 13 · see citing works

Proteomic Analysis of Skeletal Muscle and White Adipose Tissue after Aerobic Exercise Training in High Fat Diet Induced Obese Mice

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Proteome analysis using machine learning approaches and its applications to diseases

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The Small Open Reading Frame‐Encoded Peptides: Advances in Methodologies and Functional Studies

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SynBioTools: a one-stop facility for searching and selecting synthetic biology tools

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Exploration of the underlying mechanisms of isoniazid/rifampicin‐induced liver injury in mice using an integrated proteomics and metabolomics approach

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Metabolomic Changes in Rat Serum after Chronic Exposure to Glyphosate-Based Herbicide

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Introduction to Bioinformatics, AI, and ML for Pharmaceuticals

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Functional response of Acinetobacter guillouiae SFC 500-1A to tannery wastewater as revealed by a complementary proteomic approach

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Mass spectrometry based proteomics: Changing the impact of protein analysis in forensic science

Keane, R. E., Tidy, R. J., Parker, G. J., Gummer, J. P. A., & Priddis, C. (2024) · Wiley Interdisciplinary Reviews Forensic Science · doi:10.1002/wfs2.1516 · Cited by 11 · see citing works

Biomarker Discovery

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Proteomics approaches to understand cell biology and virulence of Entamoeba histolytica protozoan parasite

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Preclinical Study of Human Bone Marrow-Derived Mesenchymal Stem Cells Using a 3-Dimensional Manufacturing Setting for Enhancing Spinal Fusion

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High‐Throughput Screening of Metabolic Biomarkers and Wearable Biosensors for the Quantification of Metabolites

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