About iPNN

iPNN is a simple web navigator designed to enable search for pathway from one metabolite to another metabolite. To predict the biosynthetic pathway for given chemicals, you can just enter start and end material and click to run.

iPNN uses various biochemical reaction databases such as EBI Rhea, KEGG LIGAND, Metacyc, BRENDA. All data were integrated in iPNN and you can click each link to collect more information.

iPNN is for synthetic biologists who want to design biosynthetic pathway which produces valuable compounds. iPNN helps to discover novel synthetic pathways from all known biochemical reactions.

iPNN also provides information of genes and proteins related to biochemical reactions in the pathway. Eventually, iPNN aims to provide a platform for design of biocircuit in the integrated way.

At present, iPNN provides physical shortest pathway between two input metabolites. We have been developing a variety of algorithms including alternative pathways, organism-specific pathways, and thermodynamically reasonable pathways, etc.


iPNN is built on open source libraries. iPNN back-end is accomplished by python modules including networkX, numpy, and pyparsing. To construct iPNN user-interface, HTML, CSS, Java (JSP), and the jQuery Javascript framework were employed.

Byoungnam Min is main developer of iPNN and established web site (principal investigator: In-Geol Choi).


  • Rhea provides fundamental resuorce for constructing metabolic network
  • Marvin view provides JAVA tools for visualizing reaction
  • NetworkX provides various functions to analyze metabolic network
  • This work was supported by the Intelligent Synthetic Biology Center (2011-0031953) and the Advanced Biomass R&D Center (2011-0031353) funded by the Korean government (Ministry of Education & Science Technology)

    1. Marnix H. Medema et al. 2012. Computational tools for the synthetic design of biochemical pathways. Nature Reviews. 10:191-202
    2. Ayoun Cho et al. 2010. Prediction of novel synthetic pathways for the production of desired chemicals. BMC Systems Biology. 4:35
    3. Pablo Carbonell et al. 2011. A retrosynthetic biology approach to metabloic pathway design for therapeutic production. BMC Systems Biology. 5:122
    4. Chih-Hung Chou et al. 2009. FMM: a web server for metabolic pathway reconstruction and comparative analysis. Nucleic Acids Research. 37:129-134


    Main developer : Byoungnam Min (mbnmbn00@gmail.com)

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