The DOI matches its Crossref record; 107 of the 107 references it cites were found in a registry or an index.
The functional landscape of the human phosphoproteome
Open accessPublished version of a preprint
Abstract
Protein phosphorylation is a key post-translational modification regulating protein function in almost all cellular processes. Although tens of thousands of phosphorylation sites have been identified in human cells, approaches to determine the functional importance of each phosphosite are lacking. Here, we manually curated 112 datasets of phospho-enriched proteins, generated from 104 different human cell types or tissues. We re-analyzed the 6,801 proteomics experiments that passed our quality control criteria, creating a reference phosphoproteome containing 119,809 human phosphosites. To prioritize functional sites, we used machine learning to identify 59 features indicative of proteomic, structural, regulatory or evolutionary relevance and integrate them into a single functional score. Our approach identifies regulatory phosphosites across different molecular mechanisms, processes and diseases, and reveals genetic susceptibilities at a genomic scale. Several regulatory phosphosites were experimentally validated, including identifying a role in neuronal differentiation for phosphosites in SMARCC2, a member of the SWI/SNF chromatin-remodeling complex.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“The inferred transcription factors and kinases indicate the well-annotated players in the DNA damage response, whereas proteins with altered thermal stability reflect less annotated parts of the signaling space with strong links to the phosphoproteomic measurements which aligns with observations linking functionality of phosphosites with thermal stability (Ochoa et al, 2020; Potel et al, 2021).”
From Network integration of thermal proteome profiling with multi-omics data decodes PARP inhibition (2024) · cites this paper as Ochoa et al, 2020
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
Love, M. I., Huber, W., & Anders, S. (2014) · Genome Biology · doi:10.1186/s13059-014-0550-8 · Cited by 95,106
The Sequence Alignment/Map format and SAMtools
Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., Durbin, R., & 1000 Genome Project Data Processing Subgroup (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp352 · Cited by 62,041
PD-1 and PD-L1 Immune Checkpoint Blockade to Treat Breast Cancer
Hartkopf, A. D., Taran, F., Wallwiener, M., Walter, C. B., Krämer, B., Grischke, E., & Brucker, S. Y. (2016) · Breast Care · doi:10.1159/000453569 · Cited by 30,989
HISAT: a fast spliced aligner with low memory requirements
Kim, D., Langmead, B., & Salzberg, S. L. (2015) · Nature Methods · doi:10.1038/nmeth.3317 · Cited by 24,112
HTSeq—a Python framework to work with high-throughput sequencing data
Anders, S., Pyl, P. T., & Huber, W. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btu638 · Cited by 21,464
Cox, J., & Mann, M. (2008) · Nature Biotechnology · doi:10.1038/nbt.1511 · Cited by 14,855
The Molecular Signatures Database Hallmark Gene Set Collection
Liberzon, A., Birger, C., Thorvaldsdóttir, H., Ghandi, M., Mesirov, J. P., & Tamayo, P. (2015) · Cell Systems · doi:10.1016/j.cels.2015.12.004 · Cited by 13,807
Gene Expression Omnibus: NCBI gene expression and hybridization array data repository
Edgar, R. (2002) · Nucleic Acids Research · doi:10.1093/nar/30.1.207 · Cited by 13,288
Nishimura, R., Osako, T., Nishiyama, Y., Tashima, R., Nakano, M., Fujisue, M., Toyozumi, Y., & Arima, N. (2013) · Oncology · doi:10.1159/000353099 · Cited by 13,239
Comprehensive molecular portraits of human breast tumours
The Cancer Genome Atlas Network (2012) · Nature · doi:10.1038/nature11412 · Cited by 12,129
Cited by
Sorted by citations
Items 401–492 of 492
Morrone, S. R., Hoopmann, M. R., Shteynberg, D. D., Kusebauch, U., & Moritz, R. L. (2023) · ChemRxiv · doi:10.26434/chemrxiv-2023-qklh1-v2 · Cited by 1
Booth, K. T. A., Jangam, S. V., Chui, M. M. C., Treat, K. M., Graziani, L., Soldano, A., White, K., Christensen, C. K., Lynnes, T. C., Yamamoto, S., et al. (2023) · medRxiv · doi:10.1101/2023.07.15.23292630 · Cited by 1
Anagho, H. A., Mullari, M., Prósz, A. G., Buch-Larsen, S. C., Locard‐Paulet, M., Szállási, Z., & Nielsen, M. L. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.12.15.571635 · Cited by 1
Protein modifications and diseases
Tang, S. (2024) · Journal of Cellular Physiology · doi:10.1002/jcp.31194 · Cited by 1
Bremer, H. J., & Pflum, M. K. H. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.03.23.644825 · Cited by 1
R2HaPpY: Rapid-robust phosphotyrosine peptide enrichment using HaloTag-Src SH2 pY superbinderPreprint
Chang, A. T., Rodríguez‐Mias, R. A., Berg, M. D., Moggridge, S., & Villén, J. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.05.14.653984 · Cited by 1
Lang, B., Streit, J. O., Kriwacki, R. W., Christodoulou, J. C., & Babu, M. M. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.06.25.661537 · Cited by 1
Misek, S. A., Borgenvik, A., Christen, D., Kyrila, G., Zhang, A., Reel, S. M., Boisvert, M., Cai, K. X., Zhou, K. N., Gonzáles, E., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.08.18.670743 · Cited by 1
PERK inhibition rewires translational and CMGC protein kinase networks into an antiviral statePreprint
Shaban, M. S., Weiser, H., Weber, A., Meier‐Soelch, J., Dort, F., Mayr‐Buro, C., Poppe, M., Karl, N., Wilhelm, J., Ziebuhr, J., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.10.08.681090 · Cited by 1
Burtscher, M. L., Garrido-Rodriguez, M., Rivera Mejias, P. A., Papagiannidis, D., Becher, I., Selegato, D. M., Potel, C., Jung, F., Zimmermann, M., Saez-Rodriguez, J., et al. (2026) · bioRxiv · doi:10.64898/2026.02.09.704793
Self-citationProximity Labeling-assisted Identification of Endogenous Kinase SubstratesPreprint
Niinae, T., Imami, K., Sugiyama, N., & Ishihama, Y. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.06.09.143370
Wang, X., Jia, Q., Zhang, Q., Yang, T., Song, J., & Wang, Y. (2021) · Research Square · doi:10.21203/rs.3.rs-378437/v1
An Overview of Proteomics and Related Nanomaterials
Sun, N.-R., Deng, C.-H., & Shen, X.-Z. (2021) · Applications of Nanomaterials in Proteomics · doi:10.1007/978-981-16-5816-7_1
Jia, Q., Zhang, Q., Yang, T., Song, J., Wang, Y., & Wang, X. (2022) · doi:10.22541/au.164864441.15827512/v1
Forum: Molecular mapping of tumor heterogeneity
(2020) · Nature Biotechnology · doi:10.1038/s41587-020-0445-z
Wang, X., Jia, Q., Zhang, Q., Yang, T., Song, J., & Wang, Y. (2021) · Research Square · doi:10.21203/rs.3.rs-378437/v2
Deep Phosphoproteomic Elucidation of Metformin-Signaling in Heterogenous Colorectal Cancer CellsPreprint
Šalovská, B., Gao, E., Müller‐Dott, S., Li, W., Dugourd, A. J. F., Rosenberger, G., Sáez-Rodríguez, J., & Liu, Y. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.07.07.499038
Proteotype Co-evolution and Diversity in MammalsPreprint
Ba, Q., Hei, Y., Dighe, A., Li, W., Maziarz, J. D., Pak, I., Wang, S., Wagner, G. P., & Liu, Y. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.06.08.495293
Kauko, O., Turunen, M. M., Pihlajamaa, P., Häkkinen, A., Queiroz, R. M. L., Pääkkönen, M., Ventelä, S., Gaetani, M., Lundström, S. L., Murgia, A., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.09.27.509636
Morrone, S. R., Hoopmann, M. R., Shteynberg, D. D., Kusebauch, U., & Moritz, R. L. (2023) · ChemRxiv · doi:10.26434/chemrxiv-2023-qklh1
Burtscher, M. L., Gade, S., Garrido‐Rodríguez, M., Rutkowska, A., Werner, T., Eberl, H. C., Petretich, M., Knopf, N., Zirngibl, K., Grandi, P., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.08.15.553354
The genetic and dietary landscape of the muscle insulin signalling networkPreprint
van Gerwen, J., Masson, S. W. C., Cutler, H. B., Díaz‐Vegas, A., Potter, M., Stöckli, J., Madsen, S., Nelson, M. E., Humphrey, S. J., & James, D. E. (2023) · eLife · doi:10.7554/elife.89212.1
eLife Assessment: The genetic and dietary landscape of the muscle insulin signalling network
Bennett, A. M. (2023) · eLife · doi:10.7554/elife.89212.1.sa3
The genetic and dietary landscape of the muscle insulin signalling networkPreprint
van Gerwen, J., Masson, S. W. C., Cutler, H. B., Díaz‐Vegas, A., Potter, M., Stöckli, J., Madsen, S., Nelson, M. E., Humphrey, S. J., & James, D. E. (2024) · eLife · doi:10.7554/elife.89212.2
Nanoparticles: implications on proteome
Fawad, M., & Hakeem, K. R. (2024) · Elsevier eBooks · doi:10.1016/b978-0-323-95721-2.00005-1
Site-specific metabolic labeling reveals proteome-wide phospho-dynamicsPreprint
Alevra, M., Marrero, M. C., Kluever, V., Mandad, S., Hemandhar-Kumar, N., Pan, K., van Gerwen, J., Kabatas, S., Wildhagen, H., Ischebeck, T., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.07.23.604744
Characterization of the Phosphomimetic Mutant Y39E of a-Synuclein
Böffinger, N. M. (2024) · eDiss (Georg-August-Universität Göttingen) · doi:10.53846/goediss-10640
Díez, P., Juanes‐Velasco, P., García‐Vaquero, M. L., Droste, C., Landeira‐Viñuela, A., Alcoceba, M., Fidalgo‐Gómez, H., Misiego‐Herrero, S., Navarro‐Bailón, A., Baile, M., et al. (2025) · Molecular Oncology · doi:10.1002/1878-0261.70032
MLMarker: a machine learning framework for tissue inference and biomarker discovery
Claeys, T., van Puyenbroeck, S., Gevaert, K., & Martens, L. (2026) · Genome biology · doi:10.1186/s13059-026-04125-8
An Aryl Diazonium‐Based Enrichment Method for Deep Coverage of Monomethyllysine Proteomics
Yan, L., Zheng, M., Fan, M., Feng, S., & Wu, M. (2025) · Current Protocols · doi:10.1002/cpz1.70170
Zhao, L., Zhang, M., Zhou, J., Jia, X., Liang, X., Tan, M., & Xu, J. (2025) · ACS Pharmacology & Translational Science · doi:10.1021/acsptsci.5c00398
Unraveling Stuttering Through a Multi-Omics Lens
Marques, D. N. (2025) · Life · doi:10.3390/life15101630
Ambros, A. M., Limberg, N., Denzinger, K., Tiemann, M., Wolber, G., Riedel, S., & Rademann, J. (2026) · Chemical Communications · doi:10.1039/d5cc06914a
Sun, Y., Xia, Y., & Coulombe‐Huntington, J. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.09.26.678911
Koenig, C., Cho, H., Emdal, K. B., Piga, I., Sabatier, P., Lozano-Juárez, S., Martínez‐Val, A., & Olsen, J. V. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2025.12.05.692571
Putative role of TMEM165 in congenital cardiomyopathies
Gonçalves, P. P. (2026) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2025.1692968 · Cited by 1
Relationship between perturbation specificity and functional dispensability in yeast phosphoproteome
Han, Y., & Xia, Y. (2026) · Biophysical Journal · doi:10.1016/j.bpj.2026.01.055
Emekeeva, D. D., Chen, J., Yang, Y., Yang, J.-H., Gorshkov, M. V., & Tarasova, I. A. (2026) · Journal of Alzheimer s Disease · doi:10.1177/13872877251414414
Reliable prediction of short linear motifs in the human proteomePreprint
Pancsa, R., Fichó, E., Kálmán, Z. E., Gerdán, C., Reményi, I., Zeke, A., Tusnády, G., & Dobson, L. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.03.04.709504
Cho, B.-K., Calderon, A. Z., & Goo, Y. A. (2026) · Rapid Communications in Mass Spectrometry · doi:10.1002/rcm.70062
Molecular mechanisms of T221 phosphorylation in modulating SIK3 kinase function and ATP binding
Wang, S., Zhang, Y., Zhang, Y., Wang, Z., Yao, X., Gong, L., Li, G., & Wang, A. (2026) · Physical Chemistry Chemical Physics · doi:10.1039/d6cp00558f
Fu, L., Xu, X., & Wu, R. (2026) · Journal of the American Society for Mass Spectrometry · doi:10.1021/jasms.6c00005
Lu, K., Li, J., Hsu, Y.-C., Wei, G., Li, Z., Du, R., Jiang, Q., Sang, H., Xue, B., Pan, H., et al. (2026) · Research Square · doi:10.21203/rs.3.rs-9176742/v1
Tian, N., Xie, S., Tang, Y., Liang, J., Zhu, W., Liu, T., Sun, Y., Yang, Y., Zhang, L., Wang, D., et al. (2026) · iMetaMed · doi:10.1002/imm3.70041
Badkul, A., Xie, L., Mottaqi, M., & Xie, L. (2026) · Information · doi:10.64898/2026.04.27.721113
Bandiera, S., Bogetofte, H., Jensen, P., Hussain, R., Nischal, S. A., Říhová, L., Clowry, G. J., Larsen, M., Molnár, Z., & Carlyle, B. C. (2026) · Journal of Anatomy · doi:10.1111/joa.70170
Zhang, S., Zhang, Y., Butt, M. H., Sun, X., & Zhang, Y. (2026) · Metabolic Engineering · doi:10.1016/j.ymben.2026.05.001
Qian, Q., Peng, J., Ma, D., Liu, K., Cheng, Y., Deng, Y., Zhao, J., Su, S., Yao, Y., Qu, Y., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.05.06.721822 · Cited by 2
The phosphoproteomic landscape of the DNA damage responsePreprint
Conte, F., Ostermaier, M., Wang, J., Goss, C., Sayols, S., Chen, J.-X., Roukos, V., Graeter, F., Aponte-Santamaria, C. A., Luck, K., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.05.11.724232 · Cited by 1
Post-translational modifications as key regulators of proline metabolism
Durand, N., Savouré, A., & Lebreton, S. (2026) · Trends in Biochemical Sciences · doi:10.1016/j.tibs.2026.04.009
Li, J., Gan, H., Zhong, Y., & Liu, H. (2026) · Molecular Genetics and Genomics · doi:10.1007/s00438-026-02441-z
Liu, Q. F., Zhou, D., Wang, K., Zhang, L. X., Wang, Y., Bian, Y., Uyama, H., Zhang, Q., & Shen, Y. (2026) · Analytical Chemistry · doi:10.1021/acs.analchem.6c00684
Genomic mapping reveals cisplatin disruption of protein phosphorylation signalling genome-wide
Qi, L., Luo, Q., Hou, Y., Xu, Y., Yu, W., Liu, X., Xin, B., Huang, Y., Li, X., Zhang, Y., et al. (2026) · Metallomics · doi:10.1093/mtomcs/mfag016
Uncovering functional variants using a high-efficiency PE3-based screening platform
Huang, S., Tao, W., Li, X., Guo, J., Zhang, Y., Li, G., Zhang, P., Zhang, G., Li, G., Fan, G., et al. (2026) · Science Advances · doi:10.1126/sciadv.ady7359 · Cited by 1
Liaskos, D., Oftadeh, O., Tonini, M., Masid, M., & Vassily Hatzimanikatis, A. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.06.19.733348
Phosphorylation Patterns of Preribosomal Proteins Associated with the RNA Exosome
Almeida, F. A., Neto, V. G., Jantsch, R. B., Barros, M. R. A., Cepeda, L. P. P., Queiroz, B. R. S., Machado, A. B. E., Menezes, A. P. D. J., da Cunha, J. P., & Oliveira, C. C. (2026) · Journal of Proteome Research · doi:10.1021/acs.jproteome.6c00095
Hartmaring, Y., Wang, S., Jones, A. R., Vizcaíno, J. A., Schlaffner, C. N., & Renard, B. Y. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.06.25.733353
Self-citationMulti-layered regulatory networks driving human dopaminergic neuron differentiationPreprint
Pinar, D. M., Jing, Y., Li, H., Li, H., Coschiera, A., Kere, J., Yoshihara, M., Swoboda, P., Sahlén, P., & Varjosalo, M. T. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.06.30.735499
Scalable phosphotyrosine enrichment with SH2 superbinder enables deep profiling of EGF responses
Chang, A., Rodríguez‐Mias, R. A., Berg, M. D., Moggridge, S., & Villén, J. (2026) · The EMBO Journal · doi:10.1038/s44318-026-00843-8 · Cited by 2
Ramasamy, P., Tichshenko, N., Díaz, A., Velghe, K., Massignani, E., Vranken, W., & Martens, L. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.07.03.736340
Vaganay, C., Ling, F., Kelly, L. M., Charles, J., Meslin, P.-A., Pasquer, H., Kim, R., Passet, M., Duchmann, M., Pelissier-Menjaud, L., et al. (2026) · Science Translational Medicine · doi:10.1126/scitranslmed.adx3847
Proteomic investigation of signaling dynamics: from static maps to network rewiring
Dionne, U., Vafaee, K., Hesketh, G. G., & Gingras, A. (2026) · Bioscience Reports · doi:10.1042/bsr20250116
Ding, Y., Huang, C., Ning, S., Liu, J., Ge, Y., & Chi, Y. (2026) · Pathogens · doi:10.3390/pathogens15070754
GDF15 in Liver Fibrosis: Molecular Mechanisms, Immunoregulatory Functions, and Therapeutic Potential
Gan, X., Zhang, L., Yu, T., Jin, S., Wu, Y., Xu, R., Zhang, Y., Zhang, J., Xu, L., & Wang, X. (2026) · Biomolecules · doi:10.3390/biom16071060
Pai, A., Dcunha, L., Gopalakrishnan, A. P., Ummar, S., Rajeev, A. C., & Raju, R. (2026) · OMICS A Journal of Integrative Biology · doi:10.1177/15578100261470540
Post-translational modification of proteins in the human testis development pathway
Idris, F. P., Ferreira, L. G. A., Houston, B. J., Humphrey, S. J., Sinclair, A. H., & Ayers, K. L. (2026) · Human Reproduction Update · doi:10.1093/humupd/dmag016
la Rosa-Cogollo, I. D., Flórez-Valiente, A., Cabarcas-Herrera, C., Pérez-González, H., Rodríguez-Cavallo, E., & Méndez-Cuadro, D. (2026) · Journal of Molecular Graphics and Modelling · doi:10.1016/j.jmgm.2026.109526
An AI-enabled structural atlas decodes kinase specificity across the human proteome
Vanderwall, D., Huttlin, E. L., Mintseris, J., Yaron, T. M., Johnson, J. L., Dong, K. D., Bott, A. J., He, Y., Schroeter, C. B., Frere, G. A., et al. (2026) · Nature Biotechnology · doi:10.1038/s41587-026-03239-5 · Cited by 1
Thomas, J., Subair, S., Mahin, A., Gopalakrishnan, A. P., Shivamurthy, P. B., Rajeev, A. C., & Raju, R. (2026) · Frontiers in Systems Biology · doi:10.3389/fsysb.2026.1780024
Tumor-specific Kinase Motif Enrichment Analysis Identifies Personalized Therapeutic Cancer TargetsPreprint
Pu, T., Joughin, B. A., Desai, P. P., Forsythe, S. D., Holewinski, R. J., Remmert, K., Gasmi, B., Coleman, K., Leach, T., Johansen, A. M., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.07.31.742097
Determinants of protein phosphatase 1β substrate specificity for MyPhoNE motif-containing proteins
Poimenidou, G., Ragusa, M. J., Peti, W., & Kettenbach, A. N. (2026) · Journal of Biological Chemistry · doi:10.1016/j.jbc.2026.113392
Pai, A., Dcunha, L., Gopalakrishnan, A. P., Ummar, S., Rajeev, A. C., & Raju, R. (2026) · Frontiers in Systems Biology · doi:10.3389/fsysb.2026.1788470
Werner, L., Esmaeili, P., Ittner, E., Swenson, H., Kovács, A., Mateoiu, C., Dahm‐Kähler, P., Karlsson, P., Parris, T. Z., Levander, F., et al. (2026) · npj Precision Oncology · doi:10.1038/s41698-026-01659-9
Joseph, B. B., Sekhar, P. S., Gopalakrishnan, A. P., Mahin, A., & Raju, R. (2026) · OMICS A Journal of Integrative Biology · doi:10.1177/15578100261483317
Zhao, W., Guo, J., Li, M., Chen, C., Zhou, Z., Yuan, Y., Li, X., Zhao, M., Dong, L., Ni, J.-H., et al. (2026) · Journal of Pharmaceutical Analysis · doi:10.1016/j.jpha.2026.101786
A complex of MAST1 and 14-3-3η regulates Tau phosphorylation in the developing cortex
Antonioli, S., Heisterkamp, P., Chen, W., Anrather, D., Hartl, M., Martínez-Reza, M. F., Tripathy, R., Schutzbier, M., Mechtler, K., Keays, D. A., et al. (2026) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2617534123
Cell volume regulation in metazoans involves phosphorylation of TSC22D proteins
Lee, S. Y., Xiao, Y.-X., Aguilera-Uribe, M., Birkadze, S., Mero, P., Brown, K. R., Nguyen, N. H., Pleinis, J. M., Rodan, A. R., Subramanya, A. R., et al. (2026) · Cell Reports · doi:10.1016/j.celrep.2026.118051
Hong, S., Park, S., Kim, S., Park, Y. I., Lee, J. S., Kang, M., Lee, J., Hemberg, M., Kim, S. E., & Kim, K. (2026) · Science Advances · doi:10.1126/sciadv.aeh2362
Pretrained spectrum representations for diverse tandem mass spectrometry proteomics tasks
Sanders, J., Yilmaz, M., Russell, J. H., Bittremieux, W., Fondrie, W. E., Riley, N. M., Oh, S., & Noble, W. S. (2026) · Molecular & Cellular Proteomics · doi:10.1016/j.mcpro.2026.101673
Proteome-wide chemotype profiling reveals the cysteinome as a pan-PTM hub
Liu, K., Wang, M., Sun, L., Li, N., Chen, W., Tian, C., Chen, Y., Bai, Y., Jiang, P., Fu, L., et al. (2026) · Free Radical Biology and Medicine · doi:10.1016/j.freeradbiomed.2026.09.030
Liu, H., Tang, L., Chen, B., & Yu, J. (2026) · Journal of bone oncology · doi:10.1016/j.jbo.2026.100807
Khan, N. A., Fahma, A., Gopalakrishnan, A. P., Sambreena, A., Raju, R., & Rajeev, A. C. (2026) · BioTech · doi:10.3390/biotech15040095
Genetic determinants of protein phosphorylation in humansPreprint
Needham, E. J., Zhao, J. H., Hirschmüller, N., Wolford, C., Jiang, X., & Butterworth, A. S. (2026) · medRxiv · doi:10.64898/2026.10.17.26365814
Shahid, S. (2024) · International journal of medical and health research. · doi:10.61424/ijmhr.v2i1.1106
Functional architecture of rare protein coding variation across 786,871 exomesPreprint
Hou, K., Li, H., Nason, E., Finucane, H. K., Sunyaev, S. R., & O’Connor, L. J. (2026) · medRxiv · doi:10.64898/2026.10.16.26365771
Global phosphoproteomics uncovers PANK2 phosphorylation sites and co-phosphoregulation networks
Rajeev, A. C., Mahin, A., Gopalakrishnan, A. P., Shivamurthy, P. B., & Raju, R. (2026) · Results in Chemistry · doi:10.1016/j.rechem.2026.104004
Kinase Regulation Through Metabolic Control Points Directs Glucose Fate
Varghese, S., Shivamurthy, P. B., Pai, V. R., Soman, S., Ramesh, P., & Raju, R. (2026) · International Journal of Molecular Sciences · doi:10.3390/ijms27219402
Kinome profiling enabled development of a LATS1/2 inhibitor with wound healing potential
Tosto, F. A., Morris, P. J., Qu, Y., Evsen, L., Tawa, G. J., Tharakan, R., Scherer, B. S., Duveau, D. Y., Blivis, D., Voss, T. C., et al. (2026) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2602240123
Metadata
- Authors
- Ochoa, D., Jarnuczak, A. F., Viéitez, C., Gehre, M., Soucheray, M., Mateus, A., Kleefeldt, A. A., Hill, A., Garcia-Alonso, L., Stein, F., Krogan, N. J., Savitski, M. M., Swaney, D. L., Vizcaíno, J. A., Noh, K.-M., & Beltrao, P.
- Affiliations
- European Bioinformatics Institute (GB)
- European Molecular Biology Laboratory (DE)
- Gladstone Institutes (US)
- Corresponding author
- Ochoa, David
- ORCID
- Venue
- Nature Biotechnology
- Published
- 2019-12-09
- Volume
- 38
- Issue
- 3
- Pages
- 365-373
- ISSN
- 0733-222X (ISSN-L)
- 1087-0156
- 1546-1696
- PMC
- PMC7100915
- OpenAlex
- W2994464657
- Cited by
- 491
- References
- 106
- Citations by year
- 2026: 83 · 2025: 85 · 2024: 80 · 2023: 74 · 2022: 83 · 2021: 54 · 2020: 25 · 2019: 6
- FWCI
- 16.77
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Locations
- Nature Biotechnology (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- Wellcome Trust (WT101477MA, 101477, 208391/Z/17/Z, Z/17/Z, 208391)
- Topics
- Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Tyrosine Phosphatases
- Keywords
- protein phosphorylation, phosphosites, post-translational modification, machine learning feature selection, genetic susceptibility, SMARCC2, SWI/SNF chromatin remodeling, neuronal differentiation
- MeSH terms
- Machine Learning, Binding Sites, Cell Line, DNA-Binding Proteins, HeLa Cells, Humans, Phosphoproteins, Protein Processing, Post-Translational, Mass Spectrometry, Transcription Factors, Computational Biology, Databases, Protein, Proteomics, Neurogenesis, Data Curation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review