Mapping differential interactomes by affinity purification coupled with data-independent mass spectrometry acquisition

A comparison of normalization methods for high density oligonucleotide array data based on variance and bias

Bolstad, B. M., Irizarry, R. A., Åstrand, M., & Speed, T. P. (2003) · Bioinformatics · doi:10.1093/bioinformatics/19.2.185 · Cited by 8,185 · see citing works

A new regulatory motif in cell-cycle control causing specific inhibition of cyclin D/CDK4.

Serrano, M., Hannon, G. J., & Beach, D. (1993) · Nature · doi:10.1038/366704a0 · Cited by 3,650 · see citing works

Targeted Data Extraction of the MS/MS Spectra Generated by Data-independent Acquisition: A New Concept for Consistent and Accurate Proteome Analysis

Gillet, L. C., Navarro, P., Tate, S., Röst, H., Selevsek, N., Reiter, L., Bonner, R., & Aebersold, R. (2012) · Molecular & Cellular Proteomics · doi:10.1074/mcp.o111.016717 · Cited by 2,877 · see citing works

BET Bromodomain Inhibition as a Therapeutic Strategy to Target c-Myc

Delmore, J. E., Issa, G. C., Lemieux, M. E., Rahl, P. B., Shi, J., Jacobs, H. M., Kastritis, E., Gilpatrick, T., Paranal, R. M., Qi, J., et al. (2011) · Cell · doi:10.1016/j.cell.2011.08.017 · Cited by 2,820 · see citing works

eIF4 Initiation Factors: Effectors of mRNA Recruitment to Ribosomes and Regulators of Translation

Gingras, A., Raught, B., & Sonenberg, N. (1999) · Annual Review of Biochemistry · doi:10.1146/annurev.biochem.68.1.913 · Cited by 2,103 · see citing works

HSP90 at the hub of protein homeostasis: emerging mechanistic insights

Taipale, M., Jarosz, D. F., & Lindquist, S. (2010) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm2918 · Cited by 1,818 · see citing works

The CRAPome: a contaminant repository for affinity purification–mass spectrometry data

Mellacheruvu, D., Wright, Z., Couzens, A. L., Lambert, J.-P., St-Denis, N. A., Li, T., Miteva, Y. V., Hauri, S., Sardiu, M. E., Low, T. Y., et al. (2013) · Nature Methods · doi:10.1038/nmeth.2557 · Cited by 1,686 · see citing works

Selected reaction monitoring–based proteomics: workflows, potential, pitfalls and future directions

Picotti, P., & Aebersold, R. (2012) · Nature Methods · doi:10.1038/nmeth.2015 · Cited by 1,302 · see citing works

The Paragon Algorithm, a Next Generation Search Engine That Uses Sequence Temperature Values and Feature Probabilities to Identify Peptides from Tandem Mass Spectra

Shilov, I. V., Seymour, S. L., Patel, A. A., Loboda, A., Tang, W. H., Keating, S. P., Hunter, C. L., Nuwaysir, L. M., & Schaeffer, D. A. (2007) · Molecular & Cellular Proteomics · doi:10.1074/mcp.t600050-mcp200 · Cited by 1,299 · see citing works

A p16 INK4a -Insensitive CDK4 Mutant Targeted by Cytolytic T Lymphocytes in a Human Melanoma

Wölfel, T., Hauer, M., Schneider, J., Serrano, M., Wölfel, C., Klehmann, E., Plaen, E. D., Hankeln, T., Büschenfelde, K. M. Z., & Beach, D. (1995) · Science · doi:10.1126/science.7652577 · Cited by 1,153 · see citing works

Multi-site assessment of the precision and reproducibility of multiple reaction monitoring–based measurements of proteins in plasma

Addona, T. A., Abbatiello, S. E., Schilling, B., Skates, S. J., Mani, D. R., Bunk, D. M., Spiegelman, C. H., Zimmerman, L. J., Ham, A.-J. L., Keshishian, H., et al. (2009) · Nature Biotechnology · doi:10.1038/nbt.1546 · Cited by 1,037 · see citing works

Quantitative Analysis of Hsp90-Client Interactions Reveals Principles of Substrate Recognition

Taipale, M., Krykbaeva, I., Koeva, M., Kayatekin, C., Westover, K. D., Karras, G. I., & Lindquist, S. (2012) · Cell · doi:10.1016/j.cell.2012.06.047 · Cited by 879 · see citing works

Germline mutations in the p16INK4a binding domain of CDK4 in familial melanoma

Zuo, L., Weger, J., Yang, Q., Goldstein, A. M., Tucker, M. A., Walker, G. J., Hayward, N., & Dracopoli, N. C. (1996) · Nature Genetics · doi:10.1038/ng0196-97 · Cited by 818 · cited 1× · see citing works

Automated approach for quantitative analysis of complex peptide mixtures from tandem mass spectra

Venable, J. D., Dong, M., Wohlschlegel, J. A., Dillin, A. G., & Yates, J. R. (2004) · Nature Methods · doi:10.1038/nmeth705 · Cited by 798 · see citing works

Differential network biology

Ideker, T., & Krogan, N. J. (2012) · Molecular Systems Biology · doi:10.1038/msb.2011.99 · Cited by 784 · see citing works

High-Throughput Mapping of a Dynamic Signaling Network in Mammalian Cells

Barrios‐Rodiles, M., Brown, K. R., Ozdamar, B., Bose, R., Liu, Z., Donovan, R. S., Shinjo, F., Liu, Y., Dembowy, J., Taylor, I. W., et al. (2005) · Science · doi:10.1126/science.1105776 · Cited by 726 · see citing works

Analysis of protein complexes using mass spectrometry

Gingras, A., Gstaiger, M., Raught, B., & Aebersold, R. H. (2007) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm2208 · Cited by 709 · see citing works

Repeatability and Reproducibility in Proteomic Identifications by Liquid Chromatography−Tandem Mass Spectrometry

Tabb, D. L., Vega-Montoto, L., Rudnick, P. A., Variyath, A. M., Ham, A.-J. L., Bunk, D. M., Kilpatrick, L. E., Billheimer, D. D., Blackman, R. K., Cardasis, H. L., et al. (2010) · Journal of Proteome Research · doi:10.1021/pr9006365 · Cited by 551 · see citing works

mProphet: automated data processing and statistical validation for large-scale SRM experiments

Reiter, L., Rinner, O., Picotti, P., Hüttenhain, R., Beck, M., Brusniak, M.-Y., Hengartner, M. O., & Aebersold, R. (2011) · Nature Methods · doi:10.1038/nmeth.1584 · Cited by 532 · see citing works

The Transformation Suppressor Pdcd4 Is a Novel Eukaryotic Translation Initiation Factor 4A Binding Protein That Inhibits Translation

Yang, H.-S., Jansen, A. P., Komar, A. A., Zheng, X., Merrick, W. C., Costes, S., Lockett, S. J., Sonenberg, N., & Colburn, N. H. (2003) · Molecular and Cellular Biology · doi:10.1128/mcb.23.1.26-37.2003 · Cited by 494 · see citing works

4,5-Diarylisoxazole Hsp90 Chaperone Inhibitors: Potential Therapeutic Agents for the Treatment of Cancer

Brough, P. A., Aherne, W., Barril, X., Borgognoni, J., Boxall, K. J., Cansfield, J. E., Cheung, K.-M. J., Collins, I., Davies, N. G. M., Drysdale, M. J., et al. (2007) · Journal of Medicinal Chemistry · doi:10.1021/jm701018h · Cited by 449 · see citing works

Systematic Analysis of the Protein Interaction Network for the Human Transcription Machinery Reveals the Identity of the 7SK Capping Enzyme

Jerónimo, C., Forget, D., Bouchard, A., Li, Q., Chua, G., Poitras, C., Thérien, C., Bergeron, D., Bourassa, S., Greenblatt, J., et al. (2007) · Molecular Cell · doi:10.1016/j.molcel.2007.06.027 · Cited by 444 · see citing works

Kinase mutations in human disease: interpreting genotype–phenotype relationships

Lahiry, P., Torkamani, A., Schork, N. J., & Hegele, R. A. (2010) · Nature Reviews Genetics · doi:10.1038/nrg2707 · Cited by 420 · see citing works

Edgetic perturbation models of human inherited disorders

Zhong, Q., Simonis, N., Li, Q., Charloteaux, B., Heuze, F., Klitgord, N., Tam, S., Yu, H., Venkatesan, K., Mou, D., et al. (2009) · Molecular Systems Biology · doi:10.1038/msb.2009.80 · Cited by 359 · see citing works

Quantifying protein interaction dynamics by SWATH mass spectrometry: application to the 14-3-3 system

Collins, B. C., Gillet, L. C., Rosenberger, G., Röst, H. L., Vichalkovski, A., Gstaiger, M., & Aebersold, R. (2013) · Nature Methods · doi:10.1038/nmeth.2703 · Cited by 314 · see citing works

V600E B-Raf requires the Hsp90 chaperone for stability and is degraded in response to Hsp90 inhibitors

Grbovic, O. M., Basso, A. D., Sawai, A., Ye, Q., Friedlander, P. A., Solit, D. B., & Rosen, N. X. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0609973103 · Cited by 308 · see citing works

Temporal regulation of EGF signalling networks by the scaffold protein Shc1

Zheng, Y., Zhang, C., Croucher, D. R., Soliman, M. A., St‐Denis, N., Pasculescu, A., Taylor, L., Tate, S. A., Hardy, W. R., Colwill, K., et al. (2013) · Nature · doi:10.1038/nature12308 · Cited by 289 · see citing works

Performance Characteristics of a New Hybrid Quadrupole Time-of-Flight Tandem Mass Spectrometer (TripleTOF 5600)

Andrews, G. L., Simons, B. L., Young, J. B., Hawkridge, A. M., & Muddiman, D. C. (2011) · Analytical Chemistry · doi:10.1021/ac200812d · Cited by 283 · see citing works

Epidermal Growth Factor Receptors Harboring Kinase Domain Mutations Associate with the Heat Shock Protein 90 Chaperone and Are Destabilized following Exposure to Geldanamycins

Shimamura, T., Lowell, A. M., Engelman, J. A., & Shapiro, G. I. (2005) · Cancer Research · doi:10.1158/0008-5472.can-05-0933 · Cited by 259 · see citing works

Activated B-RAF Is an Hsp90 Client Protein That Is Targeted by the Anticancer Drug 17-Allylamino-17-Demethoxygeldanamycin

Dias, S. D. R., Friedlos, F., Light, Y., Springer, C. J., Workman, P., & Marais, R. (2005) · Cancer Research · doi:10.1158/0008-5472.can-05-2632 · Cited by 246 · see citing works

ProHits: integrated software for mass spectrometry–based interaction proteomics

Liu, G., Zhang, J., Larsen, B., Stark, C., Breitkreutz, A., Lin, Z.-Y., Breitkreutz, B.-J., Ding, Y., Colwill, K., Pasculescu, A., et al. (2010) · Nature Biotechnology · doi:10.1038/nbt1010-1015 · Cited by 243 · see citing works

Selected reaction monitoring mass spectrometry reveals the dynamics of signaling through the GRB2 adaptor

Bisson, N., James, D. A., Ivosev, G., Tate, S. A., Bonner, R. F., Taylor, L., & Pawson, T. J. (2011) · Nature Biotechnology · doi:10.1038/nbt.1905 · Cited by 222 · see citing works

Quantitative measurements of <i><scp>N</scp></i>‐linked glycoproteins in human plasma by <scp>SWATH</scp>‐<scp>MS</scp>

Liu, Y., Hüttenhain, R., Surinova, S., Gillet, L. C., Mouritsen, J., Brunner, R., Navarro, P., & Aebersold, R. (2013) · PROTEOMICS · doi:10.1002/pmic.201200417 · Cited by 204 · see citing works

Protein interactions in human genetic diseases

Schuster‐Böckler, B., & Bateman, A. G. (2008) · Genome biology · doi:10.1186/gb-2008-9-1-r9 · Cited by 125 · see citing works

Disease mutations in disordered regions—exception to the rule?

Vacic, V., & Iakoucheva, L. M. (2011) · Molecular BioSystems · doi:10.1039/c1mb05251a · Cited by 104 · see citing works

Molecular basis of inherited diseases: a structural perspective

Steward, R. E., MacArthur, M. W., Laskowski, R. A., & Thornton, J. M. (2003) · Trends in Genetics · doi:10.1016/s0168-9525(03)00195-1 · Cited by 102 · see citing works

Identification of CDK4 Sequences Involved in Cyclin D1 and p16 Binding

Coleman, K. G., Wautlet, B. S., Morrissey, D., Mulheron, J. G., Sedman, S. A., Brinkley, P., Price, S. M., & Webster, K. R. (1997) · Journal of Biological Chemistry · doi:10.1074/jbc.272.30.18869 · Cited by 100 · see citing works

Mass spectrometry approaches to study mammalian kinase and phosphatase associated proteins

Kean, M. J., Couzens, A. L., & Gingras, A. (2012) · Methods · doi:10.1016/j.ymeth.2012.06.002 · Cited by 69 · see citing works

V600E B‐Rafはその安定性にHsp90シャペロンを要求し,Hsp90阻害剤への応答として分解される

Grbovic, O. M., Basso, A. D., Sawai, A., Ye, Q., Friedlander, P., Solit, D. B., & Rosen, N. X. (2006) · Proceedings of the National Academy of Sciences · Cited by 65 · see citing works

Label-free quantitative proteomics trends for protein–protein interactions

Tate, S. A., Larsen, B. G., Bonner, R. F., & Gingras, A. (2012) · Journal of Proteomics · doi:10.1016/j.jprot.2012.10.027 · Cited by 59 · see citing works

CIF-1, a Shared Subunit of the COP9/Signalosome and Eukaryotic Initiation Factor 3 Complexes, Regulates MEL-26 Levels in the Caenorhabditis elegans Embryo

Luke-Glaser, S., Roy, M. M., Larsen, B. G., Bihan, T. L., Metalnikov, P. S., Tyers, M., Peter, M., & Pintard, L. (2007) · Molecular and Cellular Biology · doi:10.1128/mcb.01724-06 · Cited by 55 · see citing works

Beyond hairballs: The use of quantitative mass spectrometry data to understand protein–protein interactions

Gingras, A.-C., & Raught, B. (2012) · FEBS Letters · doi:10.1016/j.febslet.2012.03.065 · Cited by 34 · see citing works

A cost–benefit analysis of multidimensional fractionation of affinity purification‐mass spectrometry samples

Dunham, W. H., Larsen, B. G., Tate, S. A., Badillo, B. G., Goudreault, M., Tehami, Y., Kislinger, T., & Gingras, A. (2011) · PROTEOMICS · doi:10.1002/pmic.201000571 · Cited by 34 · see citing works

Strategies for Stalling Malignancy: Targeting Cancers Addiction to Hsp90

Prodromou, C. (2009) · Current Topics in Medicinal Chemistry · doi:10.2174/156802609789895656 · Cited by 25 · see citing works

Data‐independent acquisition‐based SWATH‐MS for quantitative proteomics: a tutorial

Ludwig, C., Gillet, L. C. J., Rosenberger, G., Amon, S., Collins, B. C., & Aebersold, R. H. (2018) · Molecular Systems Biology · doi:10.15252/msb.20178126 · Cited by 999 · 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

Multi-laboratory assessment of reproducibility, qualitative and quantitative performance of SWATH-mass spectrometry

Collins, B. C., Hunter, C. L., Liu, Y., Schilling, B., Rosenberger, G., Bader, S. L., Chan, D. W., Gibson, B. W., Gingras, A.-C., Held, J. M., et al. (2017) · Nature Communications · doi:10.1038/s41467-017-00249-5 · Cited by 576 · see citing works

A repository of assays to quantify 10,000 human proteins by SWATH-MS

Rosenberger, G., Koh, C. C., Guo, T., Röst, H. L., Kouvonen, P., Collins, B. C., Heusel, M., Liu, Y., Caron, E., Vichalkovski, A., et al. (2014) · Scientific Data · doi:10.1038/sdata.2014.31 · Cited by 413 · see citing works

Multidimensional proteomics for cell biology

Larance, M., & Lamond, A. I. (2015) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm3970 · Cited by 407 · see citing works

Robust, reproducible and quantitative analysis of thousands of proteomes by micro-flow LC–MS/MS

Bian, Y., Zheng, R., Bayer, F. P., Wong, C. J., Chang, Y.-C., Meng, C., Zolg, D. P., Reinecke, M., Zecha, J., Wiechmann, S., et al. (2020) · Nature Communications · doi:10.1038/s41467-019-13973-x · Cited by 342 · see citing works

Network biology concepts in complex disease comorbidities

Hu, J. X., Thomas, C. E., & Brunak, S. (2016) · Nature Reviews Genetics · doi:10.1038/nrg.2016.87 · Cited by 328 · see citing works

Quantifying protein interaction dynamics by SWATH mass spectrometry: application to the 14-3-3 system

Collins, B. C., Gillet, L. C., Rosenberger, G., Röst, H. L., Vichalkovski, A., Gstaiger, M., & Aebersold, R. (2013) · Nature Methods · doi:10.1038/nmeth.2703 · Cited by 314 · see citing works

Analysis of DIA proteomics data using MSFragger-DIA and FragPipe computational platform

Yu, F., Teo, G. C., Kong, A. T., Fröhlich, K., Li, G. X., Demichev, V., & Nesvizhskii, A. I. (2023) · Nature Communications · doi:10.1038/s41467-023-39869-5 · Cited by 304 · see citing works

Technical advances in proteomics: new developments in data-independent acquisition

Hu, A. K., Noble, W. S., & Wolf‐Yadlin, A. (2016) · F1000Research · doi:10.12688/f1000research.7042.1 · Cited by 258 · see citing works

Advances in targeted proteomics and applications to biomedical research

Shi, T., Song, E., Nie, S., Rodland, K., Liu, T., Qian, W., & Smith, R. D. (2016) · PROTEOMICS · doi:10.1002/pmic.201500449 · Cited by 259 · see citing works

A new inhibitor of glucose-6-phosphate dehydrogenase blocks pentose phosphate pathway and suppresses malignant proliferation and metastasis in vivo

Mele, L. L., Paino, F., Papaccio, F., Regad, T., Boocock, D. J., Stiuso, P., Lombardi, A., Liccardo, D., Aquino, G., Barbieri, A., et al. (2018) · Cell Death and Disease · doi:10.1038/s41419-018-0635-5 · Cited by 215 · see citing works

Using data‐independent, high‐resolution mass spectrometry in protein biomarker research: Perspectives and clinical applications

Sajic, T., Liu, Y., & Aebersold, R. H. (2014) · PROTEOMICS - CLINICAL APPLICATIONS · doi:10.1002/prca.201400117 · Cited by 209 · see citing works

Proteome-wide drug and metabolite interaction mapping by thermal-stability profiling

Huber, K., Olek, K., Müller, A. C., Tan, C. S. H., Bennett, K. L., Colinge, J., & Superti‐Furga, G. (2015) · Nature Methods · doi:10.1038/nmeth.3590 · Cited by 210 · see citing works

Mass spectrometry‐based protein–protein interaction networks for the study of human diseases

Richards, A., Eckhardt, M., & Krogan, N. J. (2021) · Molecular Systems Biology · doi:10.15252/msb.20188792 · Cited by 199 · see citing works

A New in Vivo Cross-linking Mass Spectrometry Platform to Define Protein–Protein Interactions in Living Cells

Kaake, R. M., Wang, X., Burke, A. M., Yu, C., Kandur, W. V., Yang, Y., Novtisky, E. J., Second, T. P., Duan, J., Kao, A., et al. (2014) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m114.042630 · Cited by 196 · see citing works

Glycoproteomic Analysis of Prostate Cancer Tissues by SWATH Mass Spectrometry Discovers N-acylethanolamine Acid Amidase and Protein Tyrosine Kinase 7 as Signatures for Tumor Aggressiveness

Liu, Y., Chen, J., Sethi, A., Li, Q. K., Chen, L., Collins, B. C., Gillet, L. C. J., Wollscheid, B., Zhang, H., & Aebersold, R. H. (2014) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m114.038273 · Cited by 187 · see citing works

HSP90AB1: Helping the good and the bad

Haase, M., & Fitze, G. (2016) · Gene · doi:10.1016/j.gene.2015.08.063 · Cited by 179 · see citing works

SWATH‐MS as a tool for biomarker discovery: From basic research to clinical applications

Anjo, S. I., Santa, C., & Manadas, B. J. (2017) · PROTEOMICS · doi:10.1002/pmic.201600278 · Cited by 177 · see citing works

Proteome-Wide Evaluation of Two Common Protein Quantification Methods

O’Connell, J. D., Paulo, J. A., O’Brien, J. J., & Gygi, S. P. (2018) · Journal of Proteome Research · doi:10.1021/acs.jproteome.8b00016 · Cited by 174 · see citing works

Recent progress in mass spectrometry proteomics for biomedical research

Li, X., Wang, W., & Chen, J. (2017) · Science China Life Sciences · doi:10.1007/s11427-017-9175-2 · Cited by 166 · see citing works

ANPELA: analysis and performance assessment of the label-free quantification workflow for metaproteomic studies

Tang, J., Fu, J., Wang, Y., Li, B., Li, Y., Yang, Q., Cui, X., Hong, J., Li, X., Chen, Y., et al. (2018) · Briefings in Bioinformatics · doi:10.1093/bib/bby127 · Cited by 168 · see citing works

Characterizing Protein–Protein Interactions Using Mass Spectrometry: Challenges and Opportunities

Smits, A. H., & Vermeulen, M. (2016) · Trends in biotechnology · doi:10.1016/j.tibtech.2016.02.014 · Cited by 162 · see citing works

Advances in data‐independent acquisition mass spectrometry towards comprehensive digital proteome landscape

Kitata, R. B., Yang, J., & Chen, Y. (2022) · Mass Spectrometry Reviews · doi:10.1002/mas.21781 · Cited by 167 · see citing works

Discovery and significance of protein-protein interactions in health and disease

Greenblatt, J. F., Alberts, B., & Krogan, N. J. (2024) · Cell · doi:10.1016/j.cell.2024.10.038 · Cited by 171 · see citing works

Systematic analysis of binding of transcription factors to noncoding variants

Yan, J., Qiu, Y., dos Santos, A. M. R., Yin, Y., Li, Y. E., Vinckier, N., Nariai, N., Benaglio, P., Raman, A., Li, X., et al. (2021) · Nature · doi:10.1038/s41586-021-03211-0 · Cited by 159 · see citing works

Regulatory Expansion in Mammals of Multivalent hnRNP Assemblies that Globally Control Alternative Splicing

Gueroussov, S., Weatheritt, R. J., O’Hanlon, D., Lin, Z., Narula, A., Gingras, A., & Blencowe, B. J. (2017) · Cell · doi:10.1016/j.cell.2017.06.037 · Cited by 154 · see citing works

Clinical applications of quantitative proteomics using targeted and untargeted data-independent acquisition techniques

Meyer, J. G., & Schilling, B. (2017) · Expert Review of Proteomics · doi:10.1080/14789450.2017.1322904 · Cited by 151 · see citing works

Adapting to stress — chaperome networks in cancer

Joshi, S., Wang, T., Araujo, T. L. S., Sharma, S., Brodsky, J. L., & Chiosis, G. (2018) · Nature reviews. Cancer · doi:10.1038/s41568-018-0020-9 · Cited by 144 · see citing works

An alternative splicing event amplifies evolutionary differences between vertebrates

Gueroussov, S., Gonatopoulos-Pournatzis, T., Irimia, M., Raj, B., Lin, Z.-Y., Gingras, A.-C., & Blencowe, B. J. (2015) · Science · doi:10.1126/science.aaa8381 · Cited by 148 · see citing works

SWATH enables precise label‐free quantification on proteome scale

Huang, Q., Lü, Y., Luo, J., Guo, L., Wang, Z., Yang, X., Jin, W., Fang, Y., Ye, J., Shan, B., et al. (2015) · PROTEOMICS · doi:10.1002/pmic.201400270 · Cited by 142 · see citing works

Common errors in mass spectrometry‐based analysis of post‐translational modifications

Kim, M., Zhong, J., & Pandey, A. (2015) · PROTEOMICS · doi:10.1002/pmic.201500355 · Cited by 146 · see citing works

On-Beads Digestion in Conjunction with Data-Dependent Mass Spectrometry: A Shortcut to Quantitative and Dynamic Interaction Proteomics

Turriziani, B., García-Muñoz, A., Pilkington, R., Raso, C., Kölch, W., & von Kriegsheim, A. (2014) · Biology · doi:10.3390/biology3020320 · Cited by 143 · see citing works

Impact of the Identification Strategy on the Reproducibility of the DDA and DIA Results

Fernández-Costa, C., Martínez‐Bartolomé, S., McClatchy, D. B., Saviola, A. J., Yu, N., & Yates, J. R. (2020) · Journal of Proteome Research · doi:10.1021/acs.jproteome.0c00153 · Cited by 118 · see citing works

MSPLIT-DIA: sensitive peptide identification for data-independent acquisition

Wang, J., Tucholska, M., Knight, J. D. R., Lambert, J., Tate, S. A., Larsen, B. G., Gingras, A., & Bandeira, N. (2015) · Nature Methods · doi:10.1038/nmeth.3655 · Cited by 119 · see citing works

Selective targeting of the stress chaperome as a therapeutic strategy

Taldone, T., Ochiana, S. O., Patel, P. D., & Chiosis, G. (2014) · Trends in Pharmacological Sciences · doi:10.1016/j.tips.2014.09.001 · Cited by 111 · see citing works

SWATH Mass Spectrometry Performance Using Extended Peptide MS/MS Assay Libraries

Wu, J. X., Song, X., Pascovici, D., Zaw, T., Care, N., Krisp, C., & Molloy, M. P. (2016) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m115.055558 · Cited by 107 · see citing works

Functional variomics and network perturbation: connecting genotype to phenotype in cancer

Yi, S. S., Lin, S., Li, Y., Zhao, W., Mills, G. B., & Sahni, N. (2017) · Nature Reviews Genetics · doi:10.1038/nrg.2017.8 · Cited by 98 · see citing works

Short GeLC‐SWATH: A fast and reliable quantitative approach for proteomic screenings

Anjo, S. I., Santa, C., & Manadas, B. J. (2014) · PROTEOMICS · doi:10.1002/pmic.201400221 · Cited by 95 · see citing works

Human protein interaction networks across tissues and diseases

Yeger‐Lotem, E., & Sharan, R. (2015) · Frontiers in Genetics · doi:10.3389/fgene.2015.00257 · Cited by 90 · see citing works

Advancing translational research and precision medicine with targeted proteomics

Uzozie, A. C., & Aebersold, R. H. (2018) · Journal of Proteomics · doi:10.1016/j.jprot.2018.02.021 · Cited by 88 · see citing works

Generation of High-Quality SWATH® Acquisition Data for Label-free Quantitative Proteomics Studies Using TripleTOF® Mass Spectrometers

Schilling, B., Gibson, B. W., & Hunter, C. L. (2017) · Methods in molecular biology · doi:10.1007/978-1-4939-6747-6_16 · Cited by 88 · see citing works

Do hypoxia/normoxia culturing conditions change the neuroregulatory profile of Wharton Jelly mesenchymal stem cell secretome?

Teixeira, F. G., Panchalingam, K. M., Anjo, S. I., Manadas, B., Pereira, R., Sousa, N., Salgado, A. J., & Behie, L. A. (2015) · Stem Cell Research &amp; Therapy · doi:10.1186/s13287-015-0124-z · Cited by 87 · see citing works

Targeted phosphoproteomics of insulin signaling using data-independent acquisition mass spectrometry

Parker, B. L., Yang, G., Humphrey, S. J., Chaudhuri, R., Ma, X., Peterman, S. M., & James, D. E. (2015) · Science Signaling · doi:10.1126/scisignal.aaa3139 · Cited by 78 · see citing works

A Primer on Concepts and Applications of Proteomics in Neuroscience

Hosp, F., & Mann, M. (2017) · Neuron · doi:10.1016/j.neuron.2017.09.025 · Cited by 77 · see citing works

Application guide for omics approaches to cell signaling

Yao, Z., Petschnigg, J., Ketteler, R., & Štagljar, I. (2015) · Nature Chemical Biology · doi:10.1038/nchembio.1809 · Cited by 76 · see citing works

Parallel Exploration of Interaction Space by BioID and Affinity Purification Coupled to Mass Spectrometry

Hesketh, G. G., Youn, J., Samavarchi‐Tehrani, P., Raught, B., & Gingras, A. (2017) · Methods in molecular biology · doi:10.1007/978-1-4939-6747-6_10 · Cited by 73 · see citing works

Untargeted, spectral library‐free analysis of data‐independent acquisition proteomics data generated using Orbitrap mass spectrometers

Tsou, C., Tsai, C., Teo, G. C., Chen, Y., & Nesvizhskii, A. I. (2016) · PROTEOMICS · doi:10.1002/pmic.201500526 · Cited by 72 · see citing works

A modular and adaptive mass spectrometry-based platform for support of bioprocess development toward optimal host cell protein clearance

Walker, D., Yang, F., Carver, J. O., Joe, K., Michels, D. A., & Yu, X. C. (2017) · mAbs · doi:10.1080/19420862.2017.1303023 · Cited by 74 · see citing works

Protein Network of the Pseudomonas aeruginosa Denitrification Apparatus

Acuña, J. M. B., Rohde, M., Wissing, J. B., Jänsch, L., Schobert, M., Molinari, G., Timmis, K. N., Jahn, M., & Jahn, D. (2016) · Journal of Bacteriology · doi:10.1128/jb.00055-16 · Cited by 72 · see citing works

Data Independent Acquisition analysis in ProHits 4.0

Liu, G., Knight, J. D. R., Zhang, J. P., Tsou, C., Wang, J., Lambert, J., Larsen, B. G., Tyers, M., Raught, B., Bandeira, N., et al. (2016) · Journal of Proteomics · doi:10.1016/j.jprot.2016.04.042 · Cited by 72 · see citing works

Quantitative affinity purification mass spectrometry: a versatile technology to study protein–protein interactions

Meyer, K., & Selbach, M. (2015) · Frontiers in Genetics · doi:10.3389/fgene.2015.00237 · Cited by 70 · see citing works

SAINTq: Scoring protein‐protein interactions in affinity purification – mass spectrometry experiments with fragment or peptide intensity data

Teo, G., Koh, H. W. L., Fermin, D., Lambert, J., Knight, J. D. R., Gingras, A., & Choi, H. (2016) · PROTEOMICS · doi:10.1002/pmic.201500499 · Cited by 67 · see citing works

GADD34 is a modulator of autophagy during starvation

Gambardella, G., Staiano, L., Moretti, M. N., Cegli, R. D., Fagnocchi, L., Tullio, G. D., Polletti, S., Braccia, C., Armirotti, A., Zippo, A., et al. (2020) · Science Advances · doi:10.1126/sciadv.abb0205 · Cited by 65 · see citing works

The Double-Edged Sword: Conserved Functions of Extracellular Hsp90 in Wound Healing and Cancer

Hance, M. W., Nolan, K. D., & Isaacs, J. S. (2014) · Cancers · doi:10.3390/cancers6021065 · Cited by 62 · see citing works

Bottom-Up Proteomics (2013–2015): Keeping up in the Era of Systems Biology

Mayne, J., Ning, Z., Zhang, X., Starr, A. E., Chen, R., Deeke, S. A., Chiang, C., Xu, B., Wen, M., Cheng, K., et al. (2015) · Analytical Chemistry · doi:10.1021/acs.analchem.5b04230 · Cited by 63 · see citing works

Protein context shapes the specificity of SH3 domain-mediated interactions in vivo

Dionne, U., Bourgault, É., Dubé, A. K., Bradley, D. T. C., Chartier, F. J.-M., Dandage, R., Dibyachintan, S., Després, P. C., Gish, G. D., Pham, N. T. H., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-21873-2 · Cited by 61 · see citing works

Interacting Network of the Gap Junction (GJ) Protein Connexin43 (Cx43) is Modulated by Ischemia and Reperfusion in the Heart*

Martins‐Marques, T., Anjo, S. I., Pereira, P., Manadas, B. J., & Girão, H. (2015) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m115.052894 · Cited by 56 · see citing works

Monoamine oxidase-A promotes protective autophagy in human SH-SY5Y neuroblastoma cells through Bcl-2 phosphorylation

Ugun‐Klusek, A., Theodosi, T. S., Fitzgerald, J. C., Burté, F., Ufer, C., Boocock, D. J., Yu‐Wai‐Man, P., Bedford, L., & Billett, E. E. (2018) · Redox Biology · doi:10.1016/j.redox.2018.10.003 · Cited by 56 · see citing works

Comparative Proteomic Analysis of Proteins Involved in Bioenergetics Pathways Associated with Human Sperm Motility

Moscatelli, N., Lunetti, P., Braccia, C., Armirotti, A., Pisanello, F., Vittorio, M. D., Zara, V., & Ferramosca, A. (2019) · International Journal of Molecular Sciences · doi:10.3390/ijms20123000 · Cited by 56 · see citing works

Quest for Missing Proteins: Update 2015 on Chromosome-Centric Human Proteome Project

Horvatovich, P. L., Lundberg, E. K., Chen, Y., Sung, T.-Y., He, F., Nice, E. C., Goode, R. J. A., Yu, S., Ranganathan, S., Baker, M. S., et al. (2015) · Journal of Proteome Research · doi:10.1021/pr5013009 · Cited by 54 · see citing works

Label-free Quantitative Analysis of Changes in Broiler Liver Proteins under Heat Stress using SWATH-MS Technology

Tang, X., Meng, Q., Gao, J., Zhang, S., Zhang, H., & Zhang, M. (2015) · Scientific Reports · doi:10.1038/srep15119 · Cited by 52 · see citing works

Mapping protein–protein interactions by mass spectrometry

Liu, X., Abad, L., Chatterjee, L., Cristea, I. M., & Varjosalo, M. T. (2024) · Mass Spectrometry Reviews · doi:10.1002/mas.21887 · Cited by 48 · see citing works

Systems cell biology

Mast, F. D., Ratushny, A. V., & Aitchison, J. D. (2014) · The Journal of Cell Biology · doi:10.1083/jcb.201405027 · Cited by 51 · see citing works

Palmitoylation targets the calcineurin phosphatase to the phosphatidylinositol 4-kinase complex at the plasma membrane

Ulengin-Talkish, I., Parson, M. A., Jenkins, M. L., Roy, J., Shih, A. Z. L., St‐Denis, N., Gulyás, G., Balla, T., Gingras, A., Várnai, P., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-26326-4 · Cited by 47 · see citing works

Reproducible quantitative proteotype data matrices for systems biology

Röst, H. L., Malmström, L., & Aebersold, R. H. (2015) · Molecular Biology of the Cell · doi:10.1091/mbc.e15-07-0507 · Cited by 46 · see citing works

The GTPase Nog1 co-ordinates the assembly, maturation and quality control of distant ribosomal functional centers

Klingauf‐Nerurkar, P., Gillet, L. C. J., Portugal-Calisto, D., Oborská‐Oplová, M., Jäger, M., Schubert, O. T., Pisano, A., Peña, C., Rao, S., Altvater, M., et al. (2020) · eLife · doi:10.7554/elife.52474 · Cited by 46 · see citing works

SECAT: Quantifying Protein Complex Dynamics across Cell States by Network-Centric Analysis of SEC-SWATH-MS Profiles

Rosenberger, G., Heusel, M., Bludau, I., Collins, B. C., Martelli, C., Williams, E. G., Xue, P., Liu, Y., Aebersold, R. H., & Califano, A. (2020) · Cell Systems · doi:10.1016/j.cels.2020.11.006 · Cited by 40 · see citing works

Multi‐omic landscaping of human midbrains identifies disease‐relevant molecular targets and pathways in advanced‐stage Parkinson's disease

Gomes, L. C., Galhoz, A., Jain, G., Roser, A., Maass, F., Carboni, E., Barski, E., Lenz, C., Lohmann, K., Klein, C., et al. (2022) · Clinical and Translational Medicine · doi:10.1002/ctm2.692 · Cited by 46 · see citing works

Tear Proteomics in Keratoconus: A Quantitative SWATH-MS Analysis

López‐López, M., Regueiro, U., Bravo, S. B., Chantada‐Vázquez, M. D. P., Varela‐Fernández, R., Ávila‐Gómez, P., Hervella, P., & Lema, I. (2021) · Investigative Ophthalmology & Visual Science · doi:10.1167/iovs.62.10.30 · Cited by 45 · see citing works

Global Lysine Acetylation in Escherichia coli Results from Growth Conditions That Favor Acetate Fermentation

Schilling, B., Basisty, N., Christensen, D. G., Sorensen, D. J., Orr, J. S., Wolfe, A. J., & Rao, C. V. (2019) · Journal of Bacteriology · doi:10.1128/jb.00768-18 · Cited by 45 · see citing works

Alzheimer’s as a Systems-Level Disease Involving the Interplay of Multiple Cellular Networks

Castrillo, J. I., & Oliver, S. G. (2016) · Methods in Molecular Biology · doi:10.1007/978-1-4939-2627-5_1 · Cited by 44 · see citing works

BRN2 suppresses apoptosis, reprograms DNA damage repair, and is associated with a high somatic mutation burden in melanomaPreprint

Herbert, K. J., Binet, R., Lambert, J., Louphrasitthiphol, P., Kalkavan, H., Sesma-Sanz, L., Robles‐Espinoza, C. D., Sarkar, S., Suer, E., Andrews, S., et al. (2019) · Genes & Development · doi:10.1101/gad.314633.118 · Cited by 45 · see citing works

Quantitative Comparison of Tandem Mass Spectra Obtained on Various Instruments

Bazsó, F. L., Ozohanics, O., Schlosser, G., Ludányi, K., Vékey, K., & Drahos, L. (2016) · Journal of the American Society for Mass Spectrometry · doi:10.1007/s13361-016-1408-y · Cited by 44 · see citing works

Effect of peptide assay library size and composition in targeted data‐independent acquisition‐MS analyses

Parker, S. J., Venkatraman, V., & Eyk, J. E. V. (2016) · PROTEOMICS · doi:10.1002/pmic.201600007 · Cited by 44 · see citing works

Mining the fecal proteome: from biomarkers to personalised medicine

Jin, P., Wang, K., Huang, C., & Nice, E. C. (2017) · Expert Review of Proteomics · doi:10.1080/14789450.2017.1314786 · Cited by 45 · see citing works

Evaluation of iTRAQ and SWATH-MS for the Quantification of Proteins Associated with Insulin Resistance in Human Duodenal Biopsy Samples

Bourassa, S., Fournier, F., Nehmé, B., Kelly, I., Tremblay, A., Lemelin, V., Lamarche, B., Couture, P., & Droit, A. (2015) · PLoS ONE · doi:10.1371/journal.pone.0125934 · Cited by 44 · see citing works

Immunocapture-Selected Reaction Monitoring Screening Facilitates the Development of ELISA for the Measurement of Native TEX101 in Biological Fluids*

Korbakis, D., Brinc, D., Schiza, C., Soosaipillai, A. R., Jarvi, K. A., Drabovich, A. P., & Diamandis, E. P. (2015) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m114.047571 · Cited by 43 · see citing works

Characterization of Cerebrospinal Fluid via Data-Independent Acquisition Mass Spectrometry

Barkovits, K., Linden, A., Galozzi, S., Schilde, L. M., Pacharra, S., Mollenhauer, B., Stoepel, N., Steinbach, S., May, C., Uszkoreit, J., et al. (2018) · Journal of Proteome Research · doi:10.1021/acs.jproteome.8b00308 · Cited by 43 · see citing works

The Core Proteome of Biofilm-Grown Clinical Pseudomonas aeruginosa Isolates

Erdmann, J., Thöming, J. G., Pohl, S., Pich, A., Lenz, C., & Häußler, S. (2019) · Cells · doi:10.3390/cells8101129 · Cited by 42 · see citing works

Optimization of Acquisition and Data-Processing Parameters for Improved Proteomic Quantification by Sequential Window Acquisition of All Theoretical Fragment Ion Mass Spectrometry

Li, S., Cao, Q., Xiao, W., Guo, Y., Yang, Y., Duan, X., & Shui, W. (2016) · Journal of Proteome Research · doi:10.1021/acs.jproteome.6b00767 · Cited by 41 · see citing works

Exercise Training in Obese Rats Does Not Induce Browning at Thermoneutrality and Induces a Muscle-Like Signature in Brown Adipose Tissue

Aldiss, P., Lewis, J. E., Lupini, I., Bloor, I. D., Chavoshinejad, R., Boocock, D. J., Miles, A. K., Ebling, F. J. P., Budge, H., & Symonds, M. E. (2020) · Frontiers in Endocrinology · doi:10.3389/fendo.2020.00097 · Cited by 41 · see citing works

SWATH™- and iTRAQ-based quantitative proteomic analyses reveal an overexpression and biological relevance of CD109 in advanced NSCLC

Zhang, F., Lin, H., Gu, A., Li, J., Liu, L., Yu, T., Cui, Y., Deng, W. W., Yan, M., Li, J., et al. (2014) · Journal of Proteomics · doi:10.1016/j.jprot.2014.03.007 · Cited by 40 · see citing works

DEAD-box helicase eIF4A2 inhibits CNOT7 deadenylation activity

Meijer, H. A., Schmidt, T., Gillen, S. L., Langlais, C., Jukes‐Jones, R., de Moor, C. H., Cain, K., Wilczynska, A., & Bushell, M. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz509 · Cited by 40 · see citing works

Recent Advances in Mass Spectrometry-Based Protein Interactome Studies

Wu, S.-W., Zhang, S., Liu, C., Fernie, A., & Yan, S.-J. (2024) · Molecular & Cellular Proteomics · doi:10.1016/j.mcpro.2024.100887 · Cited by 37 · see citing works

Identification of Topological Network Modules in Perturbed Protein Interaction Networks

Sardiu, M. E., Gilmore, J. M., Groppe, B. D., Florens, L. A., & Washburn, M. P. (2017) · Scientific Reports · doi:10.1038/srep43845 · Cited by 39 · see citing works

Hypoxia and Hypoxia-Inducible Factor-1α Regulate Endoplasmic Reticulum Stress in Nucleus Pulposus Cells

Novais, E. J., Choi, H., Madhu, V., Suyama, K., Anjo, S. I., Manadas, B. J., Shapiro, I. M., Salgado, A. J., & Risbud, M. V. (2020) · American Journal Of Pathology · doi:10.1016/j.ajpath.2020.11.012 · Cited by 39 · see citing works

Expansion of the Ion Library for Mining SWATH-MS Data through Fractionation Proteomics

Zi, J., Zhang, S., Zhou, R., Zhou, B., Xu, S., Hou, G., Tan, F., Wen, B., Wang, Q., Lin, L., et al. (2014) · Analytical Chemistry · doi:10.1021/ac501828a · Cited by 38 · see citing works

Miniaturised interaction proteomics on a microfluidic platform with ultra-low input requirements

Furlan, C., Dirks, R. A. M., Thomas, P. C., Jones, R. C., Wang, J., Lynch, M., Marks, H., & Vermeulen, M. (2019) · Nature Communications · doi:10.1038/s41467-019-09533-y · Cited by 39 · see citing works

Qualitative and Quantitative Comparison of Plasma Exosomes from Neonates and Adults

Peñas-Martínez, J., Barrachina, M. N., Cuenca‐Zamora, E. J., Luengo‐Gil, G., Bravo, S. B., Caparrós-Pérez, E., Teruel‐Montoya, R., Blanco‐Carnero, J. E., Vicente, V., García, Á. G., et al. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22041926 · Cited by 38 · see citing works

A Pathogen and a Non-pathogen Spotted Fever Group Rickettsia Trigger Differential Proteome Signatures in Macrophages

Curto, P., Santa, C., Allen, P. E., Manadas, B. J., Simões, I., & Martinez, J. J. (2019) · Frontiers in Cellular and Infection Microbiology · doi:10.3389/fcimb.2019.00043 · Cited by 37 · see citing works

The Response of Haloferax volcanii to Salt and Temperature Stress: A Proteome Study by Label‐Free Mass Spectrometry

Jevtić, Ž., Stoll, B., Pfeiffer, F., Sharma, K., Urlaub, H., Marchfelder, A., & Lenz, C. (2019) · PROTEOMICS · doi:10.1002/pmic.201800491 · Cited by 37 · see citing works

A web‐tool for visualizing quantitative protein–protein interaction data

Knight, J. D. R., Liu, G., Zhang, J. P., Pasculescu, A., Choi, H., & Gingras, A. (2014) · PROTEOMICS · doi:10.1002/pmic.201400429 · Cited by 36 · see citing works

An LXR–NCOA5 gene regulatory complex directs inflammatory crosstalk‐dependent repression of macrophage cholesterol efflux

Gillespie, M. A. K., Gold, E. S., Ramsey, S. A., Podolsky, I., Aderem, A. A., & Ranish, J. A. (2015) · The EMBO Journal · doi:10.15252/embj.201489819 · Cited by 36 · see citing works

Precise Temporal Profiling of Signaling Complexes in Primary Cells Using SWATH Mass Spectrometry

Caron, É., Roncagalli, R., Hase, T., Wolski, W., Choi, M., Menoita, M. G., Durand, S., García‐Blesa, A., Fierro-Monti, I., Sajic, T., et al. (2017) · Cell Reports · doi:10.1016/j.celrep.2017.03.019 · Cited by 36 · see citing works

Tissue and plasma proteomics for early stage cancer detection

Peng, L., Cantor, D. I., Huang, C., Wang, K., Baker, M. S., & Nice, E. C. (2018) · Molecular Omics · doi:10.1039/c8mo00126j · Cited by 36 · see citing works

Analysis of dynamic protein carbonylation in rice embryo during germination through AP‐SWATH

Zhang, H., He, D., Yu, J., Li, M., Damaris, R. N., Gupta, R., Kim, S. T., & Yang, P. (2016) · PROTEOMICS · doi:10.1002/pmic.201500248 · Cited by 35 · see citing works

Direct Phosphorylation of SRC Homology 3 Domains by Tyrosine Kinase Receptors Disassembles Ligand-Induced Signaling Networks

Dionne, U., Chartier, F. J.-M., Santos, Y. L. D. L., Lavoie, N., Bernard, D. N., Banerjee, S. L., Otis, F., Jacquet, K., Tremblay, M. G., Jain, M., et al. (2018) · Molecular Cell · doi:10.1016/j.molcel.2018.05.013 · Cited by 35 · see citing works

MCU controls melanoma progression through a redox‐controlled phenotype switch

Stejerean‐Todoran, I., Zimmermann, K., Gibhardt, C. S., Vultur, A., Ickes, C., Shannan, B., del Rio, Z. B., Wölling, A., Cappello, S., Sung, H., et al. (2022) · EMBO Reports · doi:10.15252/embr.202254746 · Cited by 33 · see citing works

Protein complex analysis: From raw protein lists to protein interaction networks

Meysman, P., Titeca, K., Eyckerman, S., Tavernier, J. H., Goethals, B., Martens, L., Valkenborg, D., & Laukens, K. (2015) · Mass Spectrometry Reviews · doi:10.1002/mas.21485 · Cited by 33 · see citing works

Protocol for mapping differential protein-protein interaction networks using affinity purification-mass spectrometry

Kaushal, P., Ummadi, M. R., Jang, G. Μ., Delgado, Y., Makanani, S. K., Alba, K., Winters, D. M., Blanc, S. F., Xu, J., Polacco, B. J., et al. (2024) · STAR Protocols · doi:10.1016/j.xpro.2024.103286 · Cited by 3 · see citing works

Quantifying protein interaction dynamics by SWATH mass spectrometry: application to the 14-3-3 system

Collins, B. C., Gillet, L. C., Rosenberger, G., Röst, H. L., Vichalkovski, A., Gstaiger, M., & Aebersold, R. (2013) · Nature Methods · doi:10.1038/nmeth.2703 · Cited by 314 · see citing works

Mapping Cancer Interactomes Using Mass Spectrometry

Gingras, A. (2013) · Europe PMC (PubMed Central)

AN INTEGRATED EXPERIMENTAL WORKFLOW TO INCREASE THROUGHPUT AND DATA ROBUSTNESS FOR ANALYSIS OF MAMMALIAN PROTEIN INTERACTION NETWORKS

Auerbach, D., Baumann, L., Uhlmann, T., Bruderer, R., Gstaiger, M., Aebersold, R. H., & Rezwan, M. (2011) · The FASEB Journal · doi:10.1096/fasebj.25.1_supplement.923.1

Computational and informatics strategies for identification of specific protein interaction partners in affinity purification mass spectrometry experiments

Nesvizhskii, A. I. (2012) · PROTEOMICS · doi:10.1002/pmic.201100537 · Cited by 93 · see citing works