Regulation Prediction

There will be a room for improvement in calculating regulation by alignment. We use global alignment in our software now, but actually in biological field, local alignment is also very important. As a result, combining global alignment with local alignment gives a better calculation. On another hand, we use BLOSM50 to score the alignment but whether this scoring mechanism is suitable to calculate regulation need to be verified. And using machine learning to optimize our scoring mechanism is our future goal. Suitable is the best! It will be a part our future work that enhancing the efficient of alignment. Better alignment method and backtrace model will make our software more excellent in giant and complex network!

Meanwhile, it is feasible to some extent that using alignment to predict the regulation, but concerning the other information about interaction such as operator, protein second structure will be more helpful. Focusing on the core of regulation is the key of analyze!

Simulation

Hill equation we use is universal in lots of field and as a result it will cause the low accuracy in network modeling. Finding an appropriate equation is really important. Chemical master equation needs a large amount of calculation, so finding a equilibrium point between accuracy and speed is an important part of our future work.

There will be a lot of uncertainty in biological process, simply mathematical equation is hard to simulate the high coupling in biology. How to decoupling and enhance the accuracy of mathematical simulation will also be a part. In the same time, it is a good attempt that adding other ways of simulation.

Converse Prediction Accuracy

PSO algorithm depends on the number of particles and precision, but it will increase the time of calculation of course. We are trying to combine different optimal method such as genetic algorithm, machine learning, annealing algorithm which could take a big part in finding best solution.

For giving a better directivity, we are trying to pick out the really useful data of prediction to the users. And users could choose which they need more efficiently.

Visualization GUI

A fantastic visualization UI is a key point of good software, more friendly control, more vivid data visualization, better network output. It will be a big part of our future work that improving the aesthetics and interactivity of GUI.