Express human protein pathway visualization


Total genes recorded: ...
Gene synonyms supported: ...
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This is a light-weight web app for common biomedical professionals to quickly look up genome pathways related to their genes of interest.

Searching among signalling pathways is often time-consuming, since protein reactome maps are often highly complex and it is difficult to find different pathways that are related to the same protein.

traditional molecular pathwa presentation

The above image shows the conventional way of showing molecular pathways. The pathway being looked for is mingled by a lot of noise.

Instead of showing long lists of protein interactions, this web app focuses on custom genes requested by you. It generates a tree of interacting genes customly plotted for your need

Genome pathway lookups will be generated for your genes specifically.

It involves 2 modules:

Module 1. Single gene pathway analysis:

Given a gene, find the up-stream and/or downstream molecular pathways. You may choose the length of pathways to search for.

demo for module 1

I think it is self-explanatory from the first sight on this map. If I input Ago2, I will get its upstream and downstream genes. I may also choose how many genes to search for and how many levels down into the molecular pathway. The search algorithm is based on academic reports: the gene interactions that are reported most will come first.

There is a button below that can generate a list of references from PubMed for all the genes listed.

demo for generate reference button demo for the list of references of module 1

Module 2: Pathway enrichment analysis:

Given a list of genes, find the pathways that connect them. If a gene cannot be connected, it will not be shown in the figure.

demo for module 2

For example, if I ran some PCR in my cell model and found TP53, AKT1, and PIK3R3 were the most significant genes, I would want to know what other genes could be involved. In a quick search on this website I would find how these genes are related in the human genome network, and figure out ERBB3, RB1, PTK2, and PIK3CA may be worth for further investigation.

Same as Single gene pathway analysis, there will also be a button appearing below the graph, which will generate a list of references for you:

demo for the list of references of module 2

You must have noticed that some genes are reported repeatedly, so they can generate a long list.


Source of Data

This web app visualizes the human protein interaction data openly available from

Gene symbols were retrieved from NCBI / GenBank

The pathway enrichment analysis module is openly available at GitHub: Gene-Enrichment

The data processing module is openly available at GitHub: Populate-website