Difference between revisions of "Team:NCTU Formosa/Description"

We establish and optimize a powerful system that is simple while accurate to predict peptides’ function, which is based on the Scoring Card Method (SCM). Instead of heavy computation and complex operation, the SCM achieves to analyze the functions of peptides with peptide sequences only.

Furthermore, we aggregate all the relative data to fulfill the integration of antifungal databases, which build the connection among the data of hosts, pathogens, and corresponding peptides. In addition, we are the first in iGEM history that not only constructed the system but also validated our prediction system with the wet web.

Moreover, IoT talk realized the application to gather weather information in farmland and predict the possibility of spore germination with cloud computing. A completion is done by NCTU_Formosa that carry out the solution of surviving in explosive information in the 21st century – Parabase, exact and fast!

Fungal diseases are crises in Taiwan which cause two-thirds of the economic loss of Taiwan’s agriculture. The method broadly used to eliminate fungal diseases is to apply chemical pesticides or to abandon entire farmlands.

Now, bio-pesticide might seem to be a good choice since it avoids all the drawbacks chemical one impacts that have caused great damage to the environment.

Yet, we are in the era of explosive information. How to find peptides with the right functions you are looking for from tons of unorganized data both effectively and accurately? It is like seeking a precious pearl in a vast ocean. Typically, a protein function analysis involves complicated calculation including template detection, alignment, or 3D modeling.

This year, we proudly announce that we are the first one to analyze by amino sequences only and consolidate our prediction with the wet lab to cure fungal diseases.

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