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hiPathDB's Running Environment
Database Content Information
Data Representation
Search hiPathDB
Search reformatted pathway
Search unified super-pathway
Manual for pathway visualization
Main window
Exploring Network
Legend for pathway element


Search hiPathDB


Reformatted pathway   TOP


The pathway-level integration is not a simple collection of pathways and gene lists, but each signaling step was remodeled to represent pathways from different sources in a coherent fashion. The website supports both physical entity and pathway queries.

Search by Physical Entity

Select the individual database on the right of the window.

Enter the interesting gene IDs in text box, and then select ID type of them

Gene ID type can be :

As genes, proteins and chemicals have lots of synonyms and homographs where two or more different biochemical entities have the same symbol, unique standard identifiers for the entities are required. We adopted the Entrez GeneID for genes and their product, PubChem compound ID for chemicals. Mapping was processed using cross-references and the process label was used as identifier for the biological process.

User can see the pathways containing the query gene.

The "Total Entities" link shows all the entities in each pathway.

Search by Pathway Name

Pathway search supports the auto-complete mode in the input box to enable users to find and select queries quickly from the recommended list.

After clicked on the relevant pathway ID, their edge relations are listed with pathway image. (For example, "apoptotic signaling in response to dna damage" of Biocarta)

HiPathDB's visualization environment has a Java applet-based framework. The visualization tightly integrated with the database is the strongest merit. The software supports diverse types of node-edge relations such as aggregation, complex formation, translocation, and biochemical reactions. The force-directed layout algorithm is optimized for pathway visualization. In addition to the basic operations of zooming and panning, coherently working multiple windows (pathway, overview, description, and information windows) facilitate network navigation and information extraction substantially. Users can delete nodes directly within network window to reduce network complexities. Visualization image can be exported as a graphics file, including PNG, JEPG, GIF, WBMP, BMP and others, as an XML or CSV file format.



Unified Super-Pathway   TOP


We implemented the entity level of pathway integration. In this gene-centric model, the entities are mapped to standard identifier, merged and unified as non-redundant data set. These non-redundant set of nodes are inter- connected into a single unified pathway like the superpathway used in BioCyc. Resulting unified pathway can be used to explore the molecular network and to identify pathway cross-talks easily.

Select the integrated pathway database on the left. Enter the interesting gene IDs in text box, and then select ID type of them.

Gene ID type can be :

As genes, proteins and chemicals have lots of synonyms and homographs where two or more different biochemical entities have the same symbol, unique standard identifiers for the entities are required. We adopted the Entrez GeneID for genes and their product, PubChem compound ID for chemicals. Mapping was processed using cross-references and the process label was used as identifier for the biological process.

User can see the pathways containing the query gene. (For example, all pathways involving BAX.)

After clicked on the right "Map and Visualize Interactions", their interactions are listed with pathway image. Similar interactions are to be merged. Interactions with matching primary participants are considered similar. Pathway related reference have external link.

The visualization tightly integrated with the database is the strongest merit. The software supports diverse types of node-edge relations such as aggregation, complex formation, translocation, and biochemical reactions. The force-directed layout algorithm is optimized for pathway visualization. In addition to the basic operations of zooming and panning, coherently working multiple windows (pathway, overview, description, and information windows) facilitate network navigation and information extraction substantially. Users can delete nodes directly within network window to reduce network complexities. Visualization image can be exported as a graphics file, including PNG, JEPG, GIF, WBMP, BMP and others, as an XML or CSV file format.

We also support node expansion in the unified super-pathways. New interactions can be added to the interaction image by expanding physical entity nodes with their further interactions (right-click on an entity node -> Expand in the menu). It also can be to add an interaction and reference list by expanding physical entity nodes.

As an illustration for utility of the unified super-pathway, we examined the BAX-mediated apoptosis process. This figure shows part of the unified pathway related to BAX, BCL2, and CYCS. Binary networks on BAX (lower right) were expanded at nodes BCL2 and CYCS in this picture. The essence of apoptosis process due to DNA damage remains to be equivalent in the signaling flow of 'DNA damage'-TP53-BAX-BCL2-CYCS-caspases as described in the BioCarta pathway. However, the unified pathway shows many additional nodes from the NCI-Nature PID and Reactome databases. NFkB, CREBBP, SP1 among the new nodes are important regulatory genes involved in various cellular processes. The NCI-Nature PID indicates that the stress response also leads to apoptosis via CYCS. Expanding at other important nodes would display many other genes and processes related to BAX, BCL2, and CYCS. Even though the details of molecular mechanism are lost in the unification process, it is evident that the unified super-pathway is useful to survey the molecular network in more comprehensive way and to identify key regulators and pathway cross-talks.