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1. Browse the database.
1.1 As shown in Figure 1, firstly, click on the "Browse" tab at the toolbar. Secondly, select the database which you want to search, then click the "Browse" button, the data at protein level will be displayed (Figure 2).
Fig.1
                Figure 1.  browse the database

1.2 The results at protein level (Figure 2) include fourteen columns.
(1) The first column shows the database which you selected before searching.
(2) The second column shows the SwissProt accessions. The database can link to uniprot website by clicking the accession number.
(3) The third column shows protein name.
(4) The fourth column shows the unique peptide counts identified of the protein.
(5) The fifth column shows the total spectra counts of the protein.
(6) The sixth column shows the percentage sequence coverage of the protein.
(7) The seventh column shows the theoretical molecular weight (MW) of the protein.
(8) The eighth column shows the theoretical isoelectric point (pI) of the protein.
(9) The ninth column represents the intensity-based absolute quantification (iBAQ) value of the protein, which were calculated by iBAQ quantification. Only 2571 proteins have iBAQ values, N/A indicates the protein with low expression values escape quantitation.
(10) The tenth column represents the absolute quantitation of the protein based on iBAQ value and albumin concentration (3.3 µg/mL). Only 2571 proteins have absolute concentrations, N/A indicates the protein with low expression values escape quantitation.
(11) The eleventh column shows tissue distribution of urinary proteins at protein expression level based on immunohistochemical staining.
(12) The twelfth column shows the peptide level information of the protein. The corresponding peptides detailed information will be shown by clicking "Show peptide" (Figure 4).
(13) The thirteen column shows the experimental image of MW and pI of the protein.

Fig.2
                Figure 2.  Browse the protein data

1.2.1 By clicking the “Tissue Distribution”, tissue distribution of urinary proteins at protein expression level based on 24,028 antibodies [1] are shown (Figure 3). The second column are Ensembl ID, the database can link to NCBI website by clicking the accession number. The third column are related tissues. There were 44 tissues studied by immunohistochemical staining at Human Protein Atlas Database. The “Level” means expression value based on antibodies, the “APE” means annotated protein expression based on more than one antibody and the "Reliability" means reliability or validation of the expression value.
Fig.3
                Figure 3.   The tissue distribution data at protein levels

1.2.2 By clicking the “Show Peptide”, results at peptide level that include 16 columns are shown in Figure 4. The first six columns shows the same content as that at protein level (Figure 2). The following seventh column shows the sequence information of the peptide. If a unique peptide has multiple spectra identifications, we actually display the information of the peptide's spectrum with the highest Mascot ion score (the ninth column). In addition, the same peptide sequence with different fixed modifications (the tenth column) or variable modifications (the eleventh column) will not be merged. The column of spectrum charge (the fourteenth column) displays all the spectra charges of the peptide.
Fig.4
                Figure 4.  The peptide data

By clicking the peptide sequence "VELAPLPSWQPVGK" (Figure 4, column 7), the detailed peptide sequence data will be shown (Figure 5). All columns of the table are the same content as that of peptide level data in Figure 4.
Fig.5
                Figure 5.  The detail peptide sequence data

1.2.3 By clicking the “Image”, experimental pI and MW distribution of all identified proteins are provided (Figure 6). GELFrEE figure (Section 1) illustrates the distribution of urinary proteins among twelve GELFrEE fractions. Section 2 shows protein abundance distribution in these twelve GELFrEE fractions based on exponentially modified protein abundance index (emPAI) values. IEF figure (Section 3) illustrates the distribution of urinary proteins among ten LP-IEF fractions. The fractions with a low concentration of proteins (fraction 7-10) were combined with fraction 6. Section 4 shows protein abundance distribution in these six LP-IEF fractions based on emPAI values.
Fig.6
                Figure 6.  Experimental pI and MW image

2. Search the database by protein accession or peptide sequence.
The query page allows searching based on protein names, Swissprot accessions and peptide sequences. As shown in Figure 7, firstly, select "protein" and input the SwissProt protein accessions in the text box, or select "peptide" and input the middle sequence of the peptide (not include in the first amino acid and the last amino acid). Secondly, select the display level of the search result, which includes protein level and peptide level as described before. Thirdly, select the database which you want to search. Then click "Query" button, and the result will be shown.
Fig.7
                Figure 7.  Search the database

3. MW-PI image of the study.
The novel section labeled ‘MW-PI image’, as shown in Figure 8, provides a succinct figure of the significant MW and pI information of all proteins. The red points represent proteins can be relatively and absolutely quantitated while the blue point represent proteins that can only be detected. A detailed information of some proteins can be showed by enlarging the image. The y axis means log2 (MW) value while x axis means pI value. Each point represents a proteins that can link to Uniprot website by clicking it.
Fig.8
                Figure 8.  MW-PI image


4. Biomarker Application
As many proteins identified in urine were served as candidate biomarkers before, the section “Biomarker Application” list application of some candidate biomarkers in diagnosis, progression and prognosis of various diseases.
Fig.8
                Figure 9.  Biomarker application


Reference:
[1] Uhlen M, Fagerberg L, Hallstrom BM, Lindskog C, Oksvold P, Mardinoglu A, et al. Proteomics. Tissue-based map of the human proteome. Science. 2015;347:1260419.


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