Convenient Accurate Tool
An integrated platform of machine learning models predicting protein properties
Nowadays, Artificial Intelligence has been devoted to various areas, and has made some magnificent contribution in Synthetic biology.
For example, Alphafold2 by Google, which can accurately predict the 3D structure by protein sequence, and some other machine learning models predicting the properties of protein sequence.
for Machine Learning Models
After a long period of researching, we found that recently there is still lack of tools that is user-friendly and can integrate existing Machine Learning models and software.
Thus, we thought whether we can design a platform which is user-friendly, lasting-support and keeping updating with more cutting-edge models.
Convenient and Accurate Tool
CAT, Convenient and Accurate Tool, is born and is based on the purpose of offering an highly-efficient software to our users.
Furthermore, we’ve not only designed a professional version for researchers, but also an educational one for students to learn more about machine learning and synthetic biology.
In the professional version, after lots of researching and collecting, we provide four properties so far, secondary structure, subcellular localization, transmembrane topo-logy and isoelectric point. Users can key in the protein sequence and obtain the properties.
We’ve designed the educational version from the scratch. From writing the content to designing the examples and format, our talented teammembers created this incredible part.
Educational version can be divided into three part, traditional mothods, the history of Artifitial intellegence and four machine learning models with some comprehensible samples.
We hope that, by using CAT educational version, we can arouse students’ interest and motivate them devoting into this interdisplinary of Synthetic Biology and Machine Learnig.