Introduction

Pathview maps, integrates and renders a wide variety of biological data on relevant pathway graphs. Here is a detailed overview. Pathview Web provides easy interactive access, and generates high quality, hyperlinked graphs. Pathview package is written in R/Bioconductor, this web interface is built on PHP with Laravel Framework and R.

Credits

Pathview web is designed and developed by Weijun Luo and his team. We also get support from Steven Blanchard, Cory Brouwer and the whole Bioinformatics Service Division (BiSD) at UNC Charlotte.

Disclaimer

Pathview is an open source software package distributed under GPLv3. Pathview downloads and uses KEGG data. Academic users may freely use the KEGG website, but other uses may require a license agreement (details at KEGG website).
We made our best efforts when developing Pathview Web server. However, we DO NOT warrant nor assume any legal responsibility for the content and function of this server.

Citations

Please cite our paper if you use this website. This will help the Pathview project in return.

• Luo W, Pant G, Bhavnasi YK, Blanchard SG, Brouwer C. Pathview Web: user friendly pathway visualization and data integration. Nucleic Acids Res, 2017, Web Server issue, doi: 10.1093/ nar/gkx372
• Luo W, Brouwer C. Pathview: an R/Biocondutor package for pathway-based data integration and visualization. Bioinformatics, 2013, 29(14):1830-1831, doi: 10.1093/bioinformatics/btt285

Please also cite GAGE paper if you are doing pathway analysis besides visualization, i.e. Pathway Selection set to Auto on the New Analysis page.

• Luo W, Friedman M, etc. GAGE: generally applicable gene set enrichment for pathway analysis. BMC Bioinformatics, 2009, 10, pp. 161, doi: 10.1186/1471-2105-10-161

Sponsors

This project is supported by an NSF ABI Development grant (Award # 1565030) and the Faculty Innovation Fund to Weijun Luo from the College of Computing and Informatics at UNC Charlotte. Sponsors also include BiSD and Department of Bioinformatics and Genomics.