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