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Unknown
(96)
Proteomics
(40)
Organisms
Aerococcus urinae NBRC 15544 = CCUG 36881
(38)
Andropogon gerardi
(38)
Bacteria
(38)
Bartonella quintana JK 31
(38)
Canis lupus familiaris
(38)
Cnidaria
(38)
Ectopseudomonas oleovorans CECT 5344
(38)
Ensifer adhaerens
(38)
Halictus scabiosae
(38)
Human immunodeficiency virus 1
(38)
Mesocricetus auratus
(38)
Miscanthus x giganteus
(38)
Morchella importuna
(38)
Mus musculus
(38)
Panicum virgatum
(38)
Pseudomonas aeruginosa PA103
(38)
Pseudomonas aeruginosa SJTD-1
(38)
Rabies virus Nishigahara RCEH
(38)
Rattus norvegicus
(38)
Rattus rattus
(38)
Rhodococcus jostii RHA1
(38)
Rhodopseudomonas palustris
(38)
Shigella
(38)
Sorghastrum nutans
(38)
Streptococcus dysgalactiae subsp. equisimilis SK1249
(38)
Streptococcus pneumoniae
(38)
Streptomyces coelicolor A3(2)
(38)
Synechocystis sp. PCC 6803
(38)
Tripsacum dactyloides
(38)
Homo sapiens
(2)
Repository
pride
(38)
iProX
(2)
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Cell culture
(18)
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(7)
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(5)
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(3)
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(2)
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(2)
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(2)
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(1)
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(1)
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(1)
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(1)
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(1)
Diffuse large B-cell lymphoma cell line
(1)
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(1)
MiaPaCa-2 cell
(1)
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(1)
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(1)
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(1)
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(1)
SW-620 cell
(1)
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(1)
Disease
Colon cancer
(4)
Chronic lymphocytic leukemia
(3)
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(2)
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(2)
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(1)
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(1)
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(1)
COVID-19
(1)
Colorectal adenocarcinoma
(1)
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(1)
Lymphoma
(1)
Non-small cell lung carcinoma
(1)
Pancreatic cancer
(1)
Renal clear cell carcinoma
(1)
Technology Type
Mass Spectrometry
(38)
Immunopeptidomics
(13)
Data-dependent acquisition
(10)
Affinity purification coupled with mass spectrometry proteomics
(9)
Bottom-up proteomics
(9)
Shotgun proteomics
(9)
Data-independent acquisition
(4)
Proteogenomics
(1)
SRM/MRM
(1)
Publication Date
2026
(10)
2025
(10)
2023
(5)
2024
(5)
2022
(4)
2021
(3)
2020
(1)
2019
(1)
2018
(1)
Release Date
2025
(16)
2022
(14)
2020
(12)
2024
(11)
2021
(11)
2023
(6)
2017
(6)
2014
(4)
2018
(3)
2009
(3)
2019
(2)
2015
(2)
2011
(2)
2016
(1)
2013
(1)
2010
(1)
2007
(1)
Lab affiliation
Department of Peptide-based Immunotherapy, Institute of Immunology, University and University Hospital Tübingen, Tübingen, Germany
(4)
Department of Immunology, Interfaculty Institute for Cell Biology, Tübingen, Germany
(2)
Université de Montréal
(2)
-Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht -Institute for Pharmaceutical Sciences, University of Utrecht, Padualaan 8, Utrecht 3584 CH, Netherlands. -Netherlands Proteomics Center, Padualaan 8, Utrecht 3584 CH, Netherlands.
(1)
1 Department of Computer Science, Hanyang University, Seoul 04763, Republic of Korea 2 Institute for Artificial Intelligence Research, Hanyang University, Seoul 04763, Republic of Korea
(1)
1. Department of Peptide-based Immunotherapy, Institute of Immunology, University and University Hospital Tübingen, Germany 2. Cluster of Excellence iFIT (EXC2180) “Image-Guided and Functionally Instructed Tumor Therapies”, University of Tübingen, Germany 3. Clinical Collaboration Unit Translational Immunology, Department of Internal Medicine, University Hospital Tübingen, Germany 4. German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), partner site Tübingen, Germany
(1)
Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Padualaan 8, 3584 CH Utrecht, the Netherlands Netherlands Proteomics Centre, Padualaan 8, 3584 CH Utrecht, the Netherlands
(1)
Charité-University Medicine Berlin
(1)
Department of Immunology, Interfaculty Institute for Cell Biology, University of Tübingen, Tübingen, Germany
(1)
Department of Medicine, School of Clinical Science, Faculty of Medicine, Nursing & Health Science, Monash University, Clayton, VIC, Australia
(1)
Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel
(1)
Department of Peptide-based Immunotherapy, Institute of Immunology, University and University Hospital Tübingen, Tübingen, BW, Germany
(1)
Department of Peptide-based Immunotherapy, University and University Hospital Tübingen, Tübingen, Germany
(1)
Department of Peptide-based Immunotherapy, University and University Hospital Tübingen, Tübingen, Germany (lab head)
(1)
Division of Immunotherapy and Immunoprevention, German Cancer Research Center (DKFZ), Heidelberg, Germany
(1)
Faculty of Biology, Technion-Israel Institute of Technology, Haifa, Israel
(1)
German Cancer Reseach Center (DKFZ)
(1)
Head Proteomics Group , Leiden University Medical Center, Center for Proteomics and Metabolomics, PO Box 9600, Postal zone P1-Q, 2300 RC Leiden, The Netherlands
(1)
INCLIVA Biomedical Research Institute
(1)
IRIC-Université de Montréal
(1)
Institute for Integrative Biology of the Cell UMR 9198 CNRS, CEA, Université Paris-Saclay 1 Avenue de la Terrasse, 91190 Gif-sur-Yvette, France
(1)
Institute for Research in Immunology and Cancer, Department of Biochemistry, Department of Chemistry, Université de Montréal, Québec, Canada H3T 1J4
(1)
Ludwig Institute for Cancer Research Department of Oncology, University hospital of Lausanne, Switzerland
(1)
Mass spectrometry
(1)
Molecular Cell Biolody, Weizmann Institute of Science.
(1)
Molecular Medicine Partnership Unit (MMPU), Heidelberg University & European Molecular Biology Laboratory (EMBL) Department of Pediatric Oncology, Hematology and Immunology, Heidelberg University & Hopp Children’s Cancer Center, National Center for Tumor Diseases (NCT)
(1)
Proteomics Center, Erasmus MC
(1)
Rudolf Virchow Center, Center for Integrative and Translational Bioimaging, University of Würzburg, Würzburg, Germany
(1)
Rudolf-Virchow Center Julius-Maximilians-Universität Würzburg Josef-Schneider Straße 2/D15 97080 Würzburg
(1)
The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School
(1)
Modification
2x(15)N labeled L-lysine
(1)
4x(15)N labeled L-arginine
(1)
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NetMHCpan, a method for MHC class I binding prediction beyond humans.
Not available
S-EPMC3319061
|
biostudies-literature
Cite
NetMHCpan-4.2: improved prediction of CD8+ epitopes by use of transfer learning and structural features.
Not available
S-EPMC12367478
|
biostudies-literature
Cite
NetMHCpan-4.1 and NetMHCIIpan-4.0: improved predictions of MHC antigen presentation by concurrent motif deconvolution and integration of MS MHC eluted ligand data.
Not available
S-EPMC7319546
|
biostudies-literature
Cite
NetMHCpan-4.0: Improved Peptide-MHC Class I Interaction Predictions Integrating Eluted Ligand and Peptide Binding Affinity Data.
Not available
S-EPMC5679736
|
biostudies-literature
Cite
NetMHCpan, a method for quantitative predictions of peptide binding to any HLA-A and -B locus protein of known sequence.
Not available
S-EPMC1949492
|
biostudies-literature
Cite
Improved pan-specific MHC class I peptide-binding predictions using a novel representation of the MHC-binding cleft environment.
Not available
S-EPMC3925504
|
biostudies-literature
Cite
Pan-specific MHC class I predictors: a benchmark of HLA class I pan-specific prediction methods.
Not available
S-EPMC2638932
|
biostudies-literature
Cite
In silico Derivation of HLA-Specific Alloreactivity Potential from Whole Exome Sequencing of Stem-Cell Transplant Donors and Recipients: Understanding the Quantitative Immunobiology of Allogeneic Transplantation.
Not available
S-EPMC4222229
|
biostudies-literature
Cite
POTN: A Human Leukocyte Antigen-A2 Immunogenic Peptides Screening Model and Its Applications in Tumor Antigens Prediction.
Not available
S-EPMC7579403
|
biostudies-literature
Cite
TruNeo: an integrated pipeline improves personalized true tumor neoantigen identification.
Not available
S-EPMC7672179
|
biostudies-literature
Cite
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