|
|
|
-
|
AI Model Training for Fucosylation Classification
|
Protein glycosylation is known to be involved in biological progresses such as cell recognition, growth, differentiation, and apoptosis. Fucosylation of glycoproteins plays an important role for structural stability and function of N-linked glycoproteins. Although many of biological and clinical studies of protein fucosylation by fucosyltransferases has been reported, structural classification of fucosylated N-glycoproteins such as core or outer isoforms remains a challenge. Here, we report for the first time the classification of N-glycopeptides as core- and outer-fucosylated types using tandem mass spectrometry (MS/MS) and machine learning algorithms such as the deep neural network (DNN) and support vector machine (SVM). Training and test sets of more than 800 MS/MS spectra of N-glycopeptides from the immunoglobulin gamma and alpha 1-acid-glycoprotein standards were selected for classification of the fucosylation types using supervised learning models. The best-performing model had an accuracy of more than 99% against manual characterization and area under the curve values greater than 0.99, which were calculated by probability scores from target and decoy datasets. Finally, this model was applied to classify fucosylated N-glycoproteins from human plasma. A total of 82N-glycopeptides, with 54 core-, 24 outer-, and 4 dual-fucosylation types derived from 54 glycoproteins, were commonly classified as the same type in both the DNN and SVM. Specifically, outer fucosylation was dominant in tri- and tetra-antennary N-glycopeptides, while core fucosylation was dominant in the mono-, bi-antennary and hybrid types of N-glycoproteins in human plasma. Thus, the machine learning methods can be combined with MS/MS to distinguish between different isoforms of fucosylated N-glycopeptides.
|
Dataset 1
|
-
|
Heeyoun Hwang
(Korea Basic Science Institute)
|
Others, Homo sapiens (Human)
|
Body Fluid: Plasma
Tissue: Others
Cell: Others
Others: standard proteins
|
Others
|
Thermo Scientific LTQ Orbitrap Elite
|
Bottom-up proteomics
|
Carbamidomethyl (C), Oxidation (M)
|
2026-05-26
|
view
Sample type, Disease, Fractionation, Digestion, Quantification, Experiment type
| Sample type |
Sample type
| Body fluid |
Tissue |
Cell |
Others |
|
Plasma
|
Others, Others
|
Others, Others
|
standard proteins
|
|
| Disease |
Others
|
| Fractionation |
Fractionation
| Method |
Separation mode |
Number of fractions |
|
Not applicable
|
Others
|
0
|
|
| Digestion |
Trypsin
|
| Quantification |
Quantification
| Labeling |
Plex |
|
No
|
0
plex
|
|
| Experiment type |
Bottom-up proteomics
|
|
|
|
|
Complete
|
Mouse heart proteomics workflow comparison for KoBMAP project
|
To establish optimal analytical conditions for high-quality data generation, mouse heart tissue was used to evaluate different combinations of sample preparation and acquisition strategies. For global proteomics, In-solution, FASP, and S-trap digestion methods were assessed in combination with both DDA and DIA acquisition modes. For phosphoproteomics, TiO₂ and IMAC enrichment methods were evaluated together with DDA and DIA acquisition strategies.
|
Dataset 1
|
-
|
Min-Sik Kim
(DGIST)
|
Mus musculus (Mouse)
|
Tissue: heart
Cell: Others
|
Others
|
Thermo Scientific Orbitrap Exploris 480
|
Bottom-up proteomics
|
Acetyl (Protein N-term), Carbamidomethyl (C), Oxidation (M)
|
2025-12-01
|
view
Sample type, Disease, Fractionation, Digestion, Quantification, Experiment type
| Sample type |
Sample type
| Body fluid |
Tissue |
Cell |
Others |
|
-
|
heart
|
Others
|
-
|
|
| Disease |
Others
|
| Fractionation |
Fractionation
| Method |
Separation mode |
Number of fractions |
|
-
|
-
|
0
|
|
| Digestion |
Trypsin
|
| Quantification |
Quantification
| Labeling |
Plex |
|
-
|
0
plex
|
|
| Experiment type |
Bottom-up proteomics
|
|
|
|
|
Complete
|
Mouse heart proteomics workflow comparison for KoBMAP project
|
To establish optimal analytical conditions for high-quality data generation, mouse heart tissue was used to evaluate different combinations of sample preparation and acquisition strategies. For global proteomics, In-solution, FASP, and S-trap digestion methods were assessed in combination with both DDA and DIA acquisition modes. For phosphoproteomics, TiO₂ and IMAC enrichment methods were evaluated together with DDA and DIA acquisition strategies.
|
Dataset 1
|
-
|
Min-Sik Kim
(DGIST)
|
Mus musculus (Mouse)
|
Tissue: heart
Cell: Others
|
Others
|
Thermo Scientific Orbitrap Exploris 480
|
Bottom-up proteomics
|
Acetyl (Protein N-term), Carbamidomethyl (C)
|
2025-12-02
|
view
Sample type, Disease, Fractionation, Digestion, Quantification, Experiment type
| Sample type |
Sample type
| Body fluid |
Tissue |
Cell |
Others |
|
-
|
heart
|
Others
|
-
|
|
| Disease |
Others
|
| Fractionation |
Fractionation
| Method |
Separation mode |
Number of fractions |
|
-
|
-
|
0
|
|
| Digestion |
-
|
| Quantification |
Quantification
| Labeling |
Plex |
|
-
|
0
plex
|
|
| Experiment type |
Bottom-up proteomics
|
|
|
|
|
Complete
|
Mouse heart proteomics workflow comparison for KoBMAP project
|
To establish optimal analytical conditions for high-quality data generation, mouse heart tissue was used to evaluate different combinations of sample preparation and acquisition strategies. For global proteomics, In-solution, FASP, and S-trap digestion methods were assessed in combination with both DDA and DIA acquisition modes. For phosphoproteomics, TiO₂ and IMAC enrichment methods were evaluated together with DDA and DIA acquisition strategies.
|
Dataset 1
|
-
|
Min-Sik Kim
(DGIST)
|
Mus musculus (Mouse)
|
Tissue: heart
Cell: Others
|
Others
|
Thermo Scientific Orbitrap Exploris 480
|
Bottom-up proteomics
|
Carbamidomethyl (C), Phospho (S), Phospho (T), Phospho (Y)
|
2025-12-02
|
view
Sample type, Disease, Fractionation, Digestion, Quantification, Experiment type
| Sample type |
Sample type
| Body fluid |
Tissue |
Cell |
Others |
|
-
|
heart
|
Others
|
-
|
|
| Disease |
Others
|
| Fractionation |
Fractionation
| Method |
Separation mode |
Number of fractions |
|
-
|
-
|
0
|
|
| Digestion |
-
|
| Quantification |
Quantification
| Labeling |
Plex |
|
-
|
0
plex
|
|
| Experiment type |
Bottom-up proteomics
|
|
|
|
|
Complete
|
Mouse heart proteomics workflow comparison for KoBMAP project
|
To establish optimal analytical conditions for high-quality data generation, mouse heart tissue was used to evaluate different combinations of sample preparation and acquisition strategies. For global proteomics, In-solution, FASP, and S-trap digestion methods were assessed in combination with both DDA and DIA acquisition modes. For phosphoproteomics, TiO₂ and IMAC enrichment methods were evaluated together with DDA and DIA acquisition strategies.
|
Dataset 1
|
-
|
Min-Sik Kim
(DGIST)
|
Mus musculus (Mouse)
|
Tissue: heart
Cell: Others
|
Others
|
Thermo Scientific Orbitrap Exploris 480
|
Bottom-up proteomics
|
Carbamidomethyl (C), Phospho (S), Phospho (T), Phospho (Y)
|
2025-12-03
|
view
Sample type, Disease, Fractionation, Digestion, Quantification, Experiment type
| Sample type |
Sample type
| Body fluid |
Tissue |
Cell |
Others |
|
-
|
heart
|
Others
|
-
|
|
| Disease |
Others
|
| Fractionation |
Fractionation
| Method |
Separation mode |
Number of fractions |
|
-
|
-
|
0
|
|
| Digestion |
Trypsin
|
| Quantification |
Quantification
| Labeling |
Plex |
|
-
|
0
plex
|
|
| Experiment type |
Bottom-up proteomics
|
|
|
|
|
Complete
|
PRM Analysis on Subcellular Localization of Nt-Arginylated Proteins in shATE1-treated HeLa.
|
The project involves the investigation of the spatial distribution of Nt-arginylated proteins by integrating subcellular fractionation with targeted proteomics (PRM) in HeLa cells. Paired peptides (Nt-arginylated vs. unmodified) for key mitochondrial proteins (SSBP1, MTHFD2, UQCRHL) were quantified under ATE1-knockdown and MGTG-treated conditions. This study demonstrated that Nt-arginylation on a transit site is strictly ATE1-dependent and significantly enriched within the mitochondrial fraction compared to the cytosol.
|
Dataset 1
|
-
|
Shinyeong Ju
(Korea Institute of Science and Technology)
|
Homo sapiens (Human)
|
Tissue: cell culture
Cell: Others
|
Others
|
Thermo Scientific Q Exactive
|
Targeted proteomics
|
Carbamidomethyl (C)
|
2025-11-19
|
view
Sample type, Disease, Fractionation, Digestion, Quantification, Experiment type
| Sample type |
Sample type
| Body fluid |
Tissue |
Cell |
Others |
|
-
|
cell culture
|
Others
|
-
|
|
| Disease |
Others
|
| Fractionation |
Fractionation
| Method |
Separation mode |
Number of fractions |
|
Not applicable
|
-
|
0
|
|
| Digestion |
Trypsin
|
| Quantification |
Quantification
| Labeling |
Plex |
|
No
|
0
plex
|
|
| Experiment type |
Targeted proteomics
|
|
|
|
|
Complete
|
Proteomic Analysis of Left Ventricular Tissue in an HFpEF Mouse Model Induced by HFD and L-NAME
|
This study established a cardiovascular disease model of heart failure with preserved ejection fraction (HFpEF) by feeding mice a high-fat diet (HFD) combined with L-NAME. Left ventricular tissue samples were collected for proteomic analysis. Proteomic profiling of the left ventricles at both 6 and 8 weeks revealed significant alterations in protein expression.
|
Dataset 1
|
-
|
Jong-Seo Kim
(Seoul National University)
|
Mus musculus (Mouse)
|
Tissue: heart
Cell: Others
|
cardiovascular system disease
|
Other MS instrument
|
Bottom-up proteomics
|
Acetyl (Protein N-term), Oxidation (M)
|
2025-09-30
|
view
Sample type, Disease, Fractionation, Digestion, Quantification, Experiment type
| Sample type |
Sample type
| Body fluid |
Tissue |
Cell |
Others |
|
-
|
heart
|
Others
|
-
|
|
| Disease |
cardiovascular system disease
|
| Fractionation |
Fractionation
| Method |
Separation mode |
Number of fractions |
|
-
|
-
|
0
|
|
| Digestion |
Trypsin
|
| Quantification |
Quantification
| Labeling |
Plex |
|
No
|
0
plex
|
|
| Experiment type |
Bottom-up proteomics
|
|
|
|
|
Complete
|
UBE2K KO mice proteomics
|
This study uncovers differential protein pattern in WT mice and UBE2K KO mice.
|
Dataset 1
|
-
|
YONG-KEUN JUNG
(Seoul National University)
|
Mus musculus (Mouse)
|
Tissue: liver
Cell: Others
|
Others
|
Thermo Scientific Orbitrap Fusion Lumos Tribrid
|
Bottom-up proteomics
|
Acetyl (K), Other modifications
|
2025-09-26
|
view
Sample type, Disease, Fractionation, Digestion, Quantification, Experiment type
| Sample type |
Sample type
| Body fluid |
Tissue |
Cell |
Others |
|
-
|
liver
|
Others
|
-
|
|
| Disease |
Others
|
| Fractionation |
Fractionation
| Method |
Separation mode |
Number of fractions |
|
-
|
-
|
0
|
|
| Digestion |
Trypsin
|
| Quantification |
Quantification
| Labeling |
Plex |
|
-
|
0
plex
|
|
| Experiment type |
Bottom-up proteomics
|
|
|
|
|
Partial
|
Omics-based precision medical technology development
|
-
|
Dataset 1
|
-
|
Kim, Tae Bum
(Asan Medical Center)
|
Homo sapiens (Human)
|
Tissue: Others
Cell: Others
|
Others
|
Other MS instrument
|
Bottom-up proteomics
|
Other modifications
|
2025-12-17
|
view
Sample type, Disease, Fractionation, Digestion, Quantification, Experiment type
| Sample type |
Sample type
| Body fluid |
Tissue |
Cell |
Others |
|
-
|
Others
|
Others
|
-
|
|
| Disease |
Others
|
| Fractionation |
Fractionation
| Method |
Separation mode |
Number of fractions |
|
-
|
-
|
0
|
|
| Digestion |
Trypsin
|
| Quantification |
Quantification
| Labeling |
Plex |
|
-
|
0
plex
|
|
| Experiment type |
Bottom-up proteomics
|
|
|
|
|
Partial
|
Omics-based precision medical technology development
|
-
|
Dataset 1
|
-
|
Kim, Tae Bum
(Asan Medical Center)
|
Homo sapiens (Human)
|
Tissue: Others
Cell: Others
|
Others
|
Other MS instrument
|
Bottom-up proteomics
|
Other modifications
|
2025-12-17
|
view
Sample type, Disease, Fractionation, Digestion, Quantification, Experiment type
| Sample type |
Sample type
| Body fluid |
Tissue |
Cell |
Others |
|
-
|
Others
|
Others
|
-
|
|
| Disease |
Others
|
| Fractionation |
Fractionation
| Method |
Separation mode |
Number of fractions |
|
-
|
-
|
0
|
|
| Digestion |
Trypsin
|
| Quantification |
Quantification
| Labeling |
Plex |
|
-
|
0
plex
|
|
| Experiment type |
Bottom-up proteomics
|
|
|
|
|
Partial
|
Omics-based precision medical technology development
|
-
|
Dataset 1
|
-
|
Kim, Tae Bum
(Asan Medical Center)
|
Homo sapiens (Human)
|
Tissue: Others
Cell: Others
|
Others
|
Other MS instrument
|
Bottom-up proteomics
|
Other modifications
|
2025-12-17
|
view
Sample type, Disease, Fractionation, Digestion, Quantification, Experiment type
| Sample type |
Sample type
| Body fluid |
Tissue |
Cell |
Others |
|
-
|
Others
|
Others
|
-
|
|
| Disease |
Others
|
| Fractionation |
Fractionation
| Method |
Separation mode |
Number of fractions |
|
-
|
-
|
0
|
|
| Digestion |
Trypsin
|
| Quantification |
Quantification
| Labeling |
Plex |
|
-
|
0
plex
|
|
| Experiment type |
Bottom-up proteomics
|
|
|
|
|
Partial
|
Omics-based precision medical technology development
|
-
|
Dataset 1
|
-
|
Kim, Tae Bum
(Asan Medical Center)
|
Homo sapiens (Human)
|
Tissue: Others
Cell: Others
|
Others
|
Other MS instrument
|
Bottom-up proteomics
|
Other modifications
|
2025-12-17
|
view
Sample type, Disease, Fractionation, Digestion, Quantification, Experiment type
| Sample type |
Sample type
| Body fluid |
Tissue |
Cell |
Others |
|
-
|
Others
|
Others
|
-
|
|
| Disease |
Others
|
| Fractionation |
Fractionation
| Method |
Separation mode |
Number of fractions |
|
-
|
-
|
0
|
|
| Digestion |
Trypsin
|
| Quantification |
Quantification
| Labeling |
Plex |
|
-
|
0
plex
|
|
| Experiment type |
Bottom-up proteomics
|
|
|
|
|
Partial
|
Omics-based precision medical technology development
|
-
|
Dataset 1
|
-
|
Kim, Tae Bum
(Asan Medical Center)
|
Homo sapiens (Human)
|
Tissue: Others
Cell: Others
|
Others
|
Other MS instrument
|
Bottom-up proteomics
|
Other modifications
|
2025-12-17
|
view
Sample type, Disease, Fractionation, Digestion, Quantification, Experiment type
| Sample type |
Sample type
| Body fluid |
Tissue |
Cell |
Others |
|
-
|
Others
|
Others
|
-
|
|
| Disease |
Others
|
| Fractionation |
Fractionation
| Method |
Separation mode |
Number of fractions |
|
-
|
-
|
0
|
|
| Digestion |
Trypsin
|
| Quantification |
Quantification
| Labeling |
Plex |
|
-
|
0
plex
|
|
| Experiment type |
Bottom-up proteomics
|
|
|
|
|
Partial
|
Omics-based precision medical technology development
|
-
|
Dataset 1
|
-
|
Kim, Tae Bum
(Asan Medical Center)
|
Homo sapiens (Human)
|
Tissue: Others
Cell: Others
|
Others
|
Other MS instrument
|
Bottom-up proteomics
|
Other modifications
|
2025-12-17
|
view
Sample type, Disease, Fractionation, Digestion, Quantification, Experiment type
| Sample type |
Sample type
| Body fluid |
Tissue |
Cell |
Others |
|
-
|
Others
|
Others
|
-
|
|
| Disease |
Others
|
| Fractionation |
Fractionation
| Method |
Separation mode |
Number of fractions |
|
-
|
-
|
0
|
|
| Digestion |
Trypsin
|
| Quantification |
Quantification
| Labeling |
Plex |
|
-
|
0
plex
|
|
| Experiment type |
Bottom-up proteomics
|
|
|
|
|
Partial
|
Omics-based precision medical technology development
|
-
|
Dataset 1
|
-
|
Kim, Tae Bum
(Asan Medical Center)
|
Homo sapiens (Human)
|
Tissue: Others
Cell: Others
|
Others
|
Other MS instrument
|
Bottom-up proteomics
|
Other modifications
|
2025-12-17
|
view
Sample type, Disease, Fractionation, Digestion, Quantification, Experiment type
| Sample type |
Sample type
| Body fluid |
Tissue |
Cell |
Others |
|
-
|
Others
|
Others
|
-
|
|
| Disease |
Others
|
| Fractionation |
Fractionation
| Method |
Separation mode |
Number of fractions |
|
-
|
-
|
0
|
|
| Digestion |
Trypsin
|
| Quantification |
Quantification
| Labeling |
Plex |
|
-
|
0
plex
|
|
| Experiment type |
Bottom-up proteomics
|
|
|
|
|
Partial
|
Omics-based precision medical technology development
|
-
|
Dataset 1
|
-
|
Kim, Tae Bum
(Asan Medical Center)
|
Homo sapiens (Human)
|
Tissue: Others
Cell: Others
|
Others
|
Other MS instrument
|
Bottom-up proteomics
|
Other modifications
|
2025-12-17
|
view
Sample type, Disease, Fractionation, Digestion, Quantification, Experiment type
| Sample type |
Sample type
| Body fluid |
Tissue |
Cell |
Others |
|
-
|
Others
|
Others
|
-
|
|
| Disease |
Others
|
| Fractionation |
Fractionation
| Method |
Separation mode |
Number of fractions |
|
-
|
-
|
0
|
|
| Digestion |
Trypsin
|
| Quantification |
Quantification
| Labeling |
Plex |
|
-
|
0
plex
|
|
| Experiment type |
Bottom-up proteomics
|
|
|
|
|
Partial
|
Omics-based precision medical technology development
|
-
|
Dataset 1
|
-
|
Kim, Tae Bum
(Asan Medical Center)
|
Homo sapiens (Human)
|
Tissue: Others
Cell: Others
|
Others
|
Other MS instrument
|
Bottom-up proteomics
|
Other modifications
|
2025-12-17
|
view
Sample type, Disease, Fractionation, Digestion, Quantification, Experiment type
| Sample type |
Sample type
| Body fluid |
Tissue |
Cell |
Others |
|
-
|
Others
|
Others
|
-
|
|
| Disease |
Others
|
| Fractionation |
Fractionation
| Method |
Separation mode |
Number of fractions |
|
-
|
-
|
0
|
|
| Digestion |
Trypsin
|
| Quantification |
Quantification
| Labeling |
Plex |
|
-
|
0
plex
|
|
| Experiment type |
Bottom-up proteomics
|
|
|
|
|
Partial
|
Omics-based precision medical technology development
|
-
|
Dataset 1
|
-
|
Kim, Tae Bum
(Asan Medical Center)
|
Homo sapiens (Human)
|
Tissue: Others
Cell: Others
|
Others
|
Other MS instrument
|
Bottom-up proteomics
|
Other modifications
|
2025-12-17
|
view
Sample type, Disease, Fractionation, Digestion, Quantification, Experiment type
| Sample type |
Sample type
| Body fluid |
Tissue |
Cell |
Others |
|
-
|
Others
|
Others
|
-
|
|
| Disease |
Others
|
| Fractionation |
Fractionation
| Method |
Separation mode |
Number of fractions |
|
-
|
-
|
0
|
|
| Digestion |
Trypsin
|
| Quantification |
Quantification
| Labeling |
Plex |
|
-
|
0
plex
|
|
| Experiment type |
Bottom-up proteomics
|
|
|
|
|
Partial
|
Omics-based precision medical technology development
|
-
|
Dataset 1
|
-
|
Kim, Tae Bum
(Asan Medical Center)
|
Homo sapiens (Human)
|
Tissue: Others
Cell: Others
|
Others
|
Other MS instrument
|
Bottom-up proteomics
|
Other modifications
|
2025-12-17
|
view
Sample type, Disease, Fractionation, Digestion, Quantification, Experiment type
| Sample type |
Sample type
| Body fluid |
Tissue |
Cell |
Others |
|
-
|
Others
|
Others
|
-
|
|
| Disease |
Others
|
| Fractionation |
Fractionation
| Method |
Separation mode |
Number of fractions |
|
-
|
-
|
0
|
|
| Digestion |
Trypsin
|
| Quantification |
Quantification
| Labeling |
Plex |
|
-
|
0
plex
|
|
| Experiment type |
Bottom-up proteomics
|
|
|
|
|
Partial
|
Omics-based precision medical technology development
|
-
|
Dataset 1
|
-
|
Kim, Tae Bum
(Asan Medical Center)
|
Homo sapiens (Human)
|
Tissue: Others
Cell: Others
|
Others
|
Other MS instrument
|
Bottom-up proteomics
|
Other modifications
|
2025-12-17
|
view
Sample type, Disease, Fractionation, Digestion, Quantification, Experiment type
| Sample type |
Sample type
| Body fluid |
Tissue |
Cell |
Others |
|
-
|
Others
|
Others
|
-
|
|
| Disease |
Others
|
| Fractionation |
Fractionation
| Method |
Separation mode |
Number of fractions |
|
-
|
-
|
0
|
|
| Digestion |
Trypsin
|
| Quantification |
Quantification
| Labeling |
Plex |
|
-
|
0
plex
|
|
| Experiment type |
Bottom-up proteomics
|
|
