| The PRIDE database and related tools and resources in 2019: improving support for quantification data Y Perez-Riverol, A Csordas, J Bai, M Bernal-Llinares, S Hewapathirana, ... Nucleic acids research 47 (D1), D442-D450, 2019 | 6186 | 2019 |
| The ProteomeXchange consortium in 2017: supporting the cultural change in proteomics public data deposition EW Deutsch, A Csordas, Z Sun, A Jarnuczak, Y Perez-Riverol, T Ternent, ... Nucleic acids research, gkw936, 2016 | 854 | 2016 |
| The ProteomeXchange consortium in 2020: enabling ‘big data’approaches in proteomics EW Deutsch, N Bandeira, V Sharma, Y Perez-Riverol, JJ Carver, ... Nucleic acids research 48 (D1), D1145-D1152, 2020 | 644 | 2020 |
| Expression Atlas update: from tissues to single cells I Papatheodorou, P Moreno, J Manning, AMP Fuentes, N George, ... Nucleic acids research 48 (D1), D77-D83, 2020 | 477 | 2020 |
| Expression Atlas: gene and protein expression across multiple studies and organisms I Papatheodorou, NA Fonseca, M Keays, YA Tang, E Barrera, W Bazant, ... Nucleic acids research 46 (D1), D246-D251, 2018 | 393 | 2018 |
| The functional landscape of the human phosphoproteome D Ochoa, AF Jarnuczak, C Viéitez, M Gehre, M Soucheray, A Mateus, ... Nature biotechnology 38 (3), 365-373, 2020 | 313 | 2020 |
| Quantifying the impact of public omics data Y Perez-Riverol, A Zorin, G Dass, MT Vu, P Xu, M Glont, JA Vizcaíno, ... Nature communications 10 (1), 3512, 2019 | 95 | 2019 |
| Analysis of intrinsic peptide detectability via integrated label-free and SRM-based absolute quantitative proteomics AF Jarnuczak, DCH Lee, C Lawless, SW Holman, CE Eyers, SJ Hubbard Journal of proteome research 15 (9), 2945-2959, 2016 | 49 | 2016 |
| Using the PRIDE Database and ProteomeXchange for Submitting and Accessing Public Proteomics Datasets AF Jarnuczak, JA Vizcaíno Current Protocols in Bioinformatics, 13.31. 1-13.31. 12, 2017 | 46 | 2017 |
| An integrated landscape of protein expression in human cancer AF Jarnuczak, H Najgebauer, M Barzine, DJ Kundu, F Ghavidel, ... Scientific data 8 (1), 115, 2021 | 44 | 2021 |
| A quantitative and temporal map of proteostasis during heat shock in Saccharomyces cerevisiae AF Jarnuczak, MG Albornoz, CE Eyers, CM Grant, SJ Hubbard Molecular Omics 14 (1), 37-52, 2018 | 20 | 2018 |
| Quantitative proteomics and network analysis of SSA1 and SSB1 deletion mutants reveals robustness of chaperone HSP70 network in Saccharomyces cerevisiae AF Jarnuczak, CE Eyers, JM Schwartz, CM Grant, SJ Hubbard Proteomics 15 (18), 3126-3139, 2015 | 15 | 2015 |
| Using deep learning to extrapolate protein expression measurements MP Barzine, K Freivalds, JC Wright, M Opmanis, D Rituma, FZ Ghavidel, ... Proteomics 20 (21-22), 2000009, 2020 | 10 | 2020 |
| Characterization of the secretome, transcriptome, and proteome of human β cell line EndoC-βH1 M Ryaboshapkina, K Saitoski, GM Hamza, AF Jarnuczak, S Pechberty, ... Molecular & Cellular Proteomics 21 (5), 2022 | 9 | 2022 |
| Proprotein convertase PCSK9 affects expression of key surface proteins in human pancreatic beta cells via intracellular and extracellular regulatory circuits K Saitoski, M Ryaboshapkina, GM Hamza, AF Jarnuczak, C Berthault, ... Journal of Biological Chemistry 298 (7), 2022 | 6 | 2022 |
| Integrative omic profiling reveals unique hypoxia induced signatures in gastric cancer associated myofibroblasts H Najgebauer, AF Jarnuczak, A Varro, CM Sanderson Cancers 11 (2), 263, 2019 | 5 | 2019 |
| Quantitative proteomics data in the public domain: challenges and opportunities AF Jarnuczak, T Ternent, JA Vizcaíno Mass Spectrometry of Proteins: Methods and Protocols, 217-235, 2019 | 5 | 2019 |
| Model Parameterization with Quantitative Proteomics: Case Study with Trehalose Metabolism in Saccharomyces cerevisiae CF Yap, M Garcia-Albornoz, AF Jarnuczak, SJ Hubbard, JM Schwartz Processes 9 (1), 139, 2021 | 3 | 2021 |
| PCSK9 affects expression of key surface proteins in human pancreatic beta cells through intra-and extracellular regulatory circuits K Saitoski, M Ryaboshapkina, GM Hamza, AF Jarnuczak, C Berthault, ... bioRxiv, 2021.09. 28.461975, 2021 | 1 | 2021 |
| Proteomics of prostate cancer serum and plasma using low and high throughput approaches GM Hamza, R Raghunathan, S Ashenden, B Zhang, E Miele, ... Clinical Proteomics 21 (1), 21, 2024 | | 2024 |
