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

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<h1>AI Green Fingers</h1>
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<h2>Abstract:</h2>
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<p>&nbsp;&nbsp;Fungus is the major disease for plants and has caused a tremendous financial loss in agriculture. We aim to use databases to find effective and also harmless anti-fungal peptides, with IOT forecast system to save fungus-infected plants. We hope to solve both the fungal and environmental hazards, help our farmers, and put sustainable development into practice through setting up green agriculture.<br></p>
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<h2>Project:</h2>
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<h4>Databases for Peptide Choosing</h4>
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&nbsp;&nbsp;First we connect four databases to know the relations among the whole fungal infection process.<br></p>
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&nbsp;&nbsp;Then, we use sequence analysis to screen peptides in databases, grouping them by different conserved domains, followed by filtering with other conditions like peptide length and whether they are toxic to E. Coli in the hopes of choosing the final peptides.</p>
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<h4>IOT Device for Advanced Application</h4>
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&nbsp;&nbsp;we use IOT device to connect the information of weather, humidity, temperature, and others, and build a model that can predict the incidence of disease.</p>
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&nbsp;&nbsp;Furthermore, we design the smartphone application to bridge users with IoT device. We aim to use IOT device to record and update all the data in each farm for each user. In the end, we hope to build an immediately updating and customized model for every single farmer in need. </p>
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<div class="des_head"> <img src="https://static.igem.org/mediawiki/2017/d/d4/Description_head.png" width="100%"> </div>
  
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<p>MiAMP1:bind to B-(1,3)-glucans in fungal cell wall.
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LaLTP: bind to the lipid on the cell membrane of the pathogen, causing permeabilization of the membrane.
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    <p>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.<br><br> 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.<br><br> 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!</p>
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RsAFP2: interact with a kind of sphigolipid on the cell membrane of the pathogen, then induces cell death.
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Weatwin-1: contains a Barwin domain which was related to ROS production in fungal hyphae.</p>
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    <p>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.<br><br> 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.<br><br> 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.<br></p>
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    <p>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. </p>
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Revision as of 10:33, 13 October 2017

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Untitled Document

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.

Untitled Document