- The translation of high-throughput gene expression data into biologically meaningful knowledge remains a bottleneck. Previously, we developed a novel computational algorithm, PATHOME (pathway and transcriptome), for detecting differentially expressed biological pathways. This algorithm employs straightforward statistical tests to evaluate the significance of differential expression patterns along subpathways.
- In our previous publication (Oncogene (2014) 33, 4941–4951), we applied the algorithm to gene expression data sets of gastric cancer (GC), identifying HNF4α-WNT5A regulation in the cross-talk between the AMPK metabolic pathway and the WNT signaling pathway. Also, we identified WNT5A as a novel potential therapeutic target for GC.
- For providing our algorithm to the biomedical society, we implemented the algorithm into a web server, called PATHOME-drug.
Extraction of network from big data repository and its visualization.
Note: This section contains some parts of our previous publication (Oncogene (2014), 33, 4941-4951) under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.