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1.
Figure 7

Figure 7. From: Reactome Pathway Analysis to Enrich Biological Discovery in Proteomics Datasets.

BioMart. Results of a BioMart query to find all human pathways in Reactome and to retrieve the UniProt annotations for the physical entities of the pathways.

Robin Haw, et al. Proteomics. ;11(18):3598-3613.
2.
Figure 1

Figure 1. From: Reactome Pathway Analysis to Enrich Biological Discovery in Proteomics Datasets.

The Reactome website (www.reactome.org) homepage. A navigation bar and the side panel to the left provide access to the pathway data and pathway analysis tools.

Robin Haw, et al. Proteomics. ;11(18):3598-3613.
3.
Figure 3

Figure 3. From: Reactome Pathway Analysis to Enrich Biological Discovery in Proteomics Datasets.

Simple and Advanced Search. (A) Results for a simple query for ‘TPI1’ protein name. (B) The query form for the Advanced search. The search modes, include i) ‘with EXACT PHRASE ONLY’: returns hits that contain the exact query phrase; ii) ‘matching REGULAR EXPRESSION’: treats the query phrase as a PERL regular expression and returns hits that contain the query words, even as a substring; iii) ‘with ALL of the words’: returns hits that contain all of the query words in any order; iv) with ANY of the words: returns hits to any word in the query phrase; v) ‘with the EXACT PHRASE’: returns only those hits that exactly MATCH the query phrase; vi) ‘!=’: returns hits that do NOT MATCH query phrase; vii) ‘with no value’: returns hits for which the selected field of a given class has no value; and viii) ‘with any value’: returns hits for which the selected field of a given Class has any value (not zero or blank).

Robin Haw, et al. Proteomics. ;11(18):3598-3613.
4.
Figure 4

Figure 4. From: Reactome Pathway Analysis to Enrich Biological Discovery in Proteomics Datasets.

Pathway Analysis. (A) Results table for the “ID mapping and pathway assignment”. The sortable table contains one row for each Reactome pathway and four columns: the user-supplied ID, the corresponding UniProt ID, the species name, and names of pathways in which this ID can be found. The names/IDs in the last two columns are clickable links that take the user to a diagram of the named pathway. (B) The results for the ‘overrepresentation analysis” are presented as a list of clickable links of enriched events. The warmer the colour, the higher the level of overrepresentation in the given pathway. Clicking on the “+” next to the pathway name gives access to the user-supplied identifiers that are found in the pathway, along with the corresponding UniProt IDs.

Robin Haw, et al. Proteomics. ;11(18):3598-3613.
5.
Figure 2

Figure 2. From: Reactome Pathway Analysis to Enrich Biological Discovery in Proteomics Datasets.

The Reactome Pathway Browser and Molecular Interaction Overlays. (A) The main features of the Pathway Browser are the ‘Search” bar at the top, the ‘Pathways” panel on the left, the ‘Visualization” panel on the right and a ‘Details” panel. A description of any reaction or pathway in the pathway diagrams can be displayed below the diagram in the ‘Details” panel by selecting the event within the diagram. Right-clicking the mouse whilst the cursor is over a physical entity displays the context sensitive menus. (B) Protein-protein interactions are displayed in the Pathway Browser for SHC1 [cytosol] and SHP2 [cytosol] physical entities. (C) Selecting ‘Other Pathways” displays additional Reactome pathways that contain the highlighted physical entity. Navigating to the additional pathway is achieved by clicking the pathway name. (D) Selecting ‘Participating Molecules” displays additional components of the macromolecular complex. Navigating to the component is achieved by clicking the entity name.

Robin Haw, et al. Proteomics. ;11(18):3598-3613.
6.
Figure 6

Figure 6. From: Reactome Pathway Analysis to Enrich Biological Discovery in Proteomics Datasets.

Species Comparison Tool. (A) Results for the comparison of human and mouse pathways. Each row in the table is a pathway; the columns are pathway name, model organism name, number of proteins in the human pathway, number of orthologous proteins in the inferred model organism pathway, a graphical representation of the ratio of these two values, and a “View” button that creates a pathway diagram. ‘Sort” buttons at the top of each column allow the table to be re-ordered according to cell contents in that column. (B) The pathway browser displaying the comparison of the human and mouse DNA Damage Bypass pathways. Physical entities in the pathway diagram are colour-coded: gray, no match; black, a complex (multicomponent) entity; and yellow, the protein’s ortholog is present in human.

Robin Haw, et al. Proteomics. ;11(18):3598-3613.
7.
Figure 5

Figure 5. From: Reactome Pathway Analysis to Enrich Biological Discovery in Proteomics Datasets.

Expression Analysis. The results table for the Expression Analysis. (A) The sortable table contains one row for each Reactome pathway and six columns: Name of the pathway, Species of presented results, Total number of proteins in pathway, Number of proteins in the user-supplied data that fall into the pathway, Graphical representation of the ratio of these 2 values, and a “View” button that creates a pathway diagram. (B) The pathway browser displaying the coloured physical entities that correspond to expression values of the experimental data. The nodes in this diagram are colour-coded: gray, no match; black, a (multicomponent) complex entity; and other colours represent expression levels. If the numerical data are a time series, the grey bar at the bottom of the coloured pathway diagram allows the user to step through time points and visualize changes in expression levels with time of the individual genes involved in the pathway.

Robin Haw, et al. Proteomics. ;11(18):3598-3613.

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