Take a gNAP before wearing your gloves! Genetic Network Analyze and Predict
The sketch and final GUI of gNAP!
We compare the result of our software with gene expression profile in literature.
We are USTC-Software!




Our application aims to simulate genetic networks. The application analyzes the stability of genetic networks after introduction of exogenous genes. Meanwhile, given the specific purposes of the original network, the application traces the regulative process back and gives possible regulative patterns of new gene.


The software is comprised of several modules as shown below:Introduction of modules:

1 Data Fetching
2 Alignment to Get New Regulation
3 Suggestion of New Gene
4 Simulation Network


Synthetic biology has been working on transforming target organisms, which usually means integrating new genes with an available network to achieve a high expression level of certain compounds. Nevertheless, the new-integrated genes are always not the original parts of the target metabolic network, so it is hard to predict how the new genes will affect the network. In some cases, new genes may even lead the network to a breakdown unexpected by wet lab experimenter. On the other hand, some wet lab experimenters also expect that target organisms could increase some original gene’s expression. As a reference to those experiment, our software put a virtual gene into the network and figure out its best regulation. To achieve wet lab’s purpose, experimenter could find a specific gene based on our prediction regulation. Lots of simulations of metabolic networks have been done with various methods. Most of them concentrate on the network itself and some of them analyze those network’s stability, robustness and Flux Balance Analysis (FBA).


The software provides a great model as a reference before wet lab experiments. It provides suggestions on both specific practicality and input of exogenous gene. Meanwhile, the software is comprised of separate modules, which can be customized for different database and optimized as the amount of users grows. Previously, we could not find any specific work on the simulation and analysis of the newly introduced genes’ impact on regulation networks, and also those softwares were unavailable, which makes our software an innovation in the field. Algorithmically, the software aims to complete the simulation based on a small amount of lab data as possible.