The 17 Sustainable Development Goals (SDGs) were adapted by all UN Member States in 2015 which call for actions “to end poverty, protect the planet and improve the lives and prospects of everyone, everywhere” and are set to by achieved by 2030[1].
As iGEMers, we have the responsibility and passion to participate in developing solutions towards meeting the SDGs. From project selection to researching and implementation, we take the sustainable development issues into account and try to match the goals when we design CAT’s functions. When CAT was born, it directly support #4 Quality Education and #9 Industries, Innovation and Infrastructure.
Team:USTC-Software/Sustainable
Sustainable
Overview
We hope that CAT will contribute to the achievement of these goals and the machine learning for protein prediction can help to change the world.
Goal 4: Quality Education
Access to quality education is the foundation of improving people's lives and achieving sustainable development. We believe, and it has been proven, that education is one of the greatest drivers of sustainable development, and therefore inclusive, quality education for all must be achieved.
During the development of CAT, we realized that CAT, the online tool software for predicting proteins using machine learning methods, could serve as a window for self-learning knowledge, stimulate users' interest in learning bioinformatics and encourage them to study more relevant works. Consequently, we have developed CAT educational version and designed educational content for it. The educational version content is suitable for high school students and above.
By using CAT educational version, users can learn about Traditional Biological Methods and Machine Learning:
- Traditional Biological Methods: experimental methods which depends on different protein properties, such as fluorescent protein in situ localization method for subcellular localization; X-ray diffraction pattern method, nuclear magnetic resonance (NMR), and cryo EM methods for transmembrane topology prediction.
- Machine Learning Methods: the history of machine learning, basic ML models and models uesd in CAT, etc.
After learning these knowledges, users will know the pros and cons of each, traditional methods and machine learning methods.
We believe that with CAT educational version, users will be able to learn about biology and machine learning in an intuitive yet fun way. In the future, more people can start using professional version of CAT to conduct their own exploration and research.
Since 2020, online education has become a necessary and mainstream form of education as a result of the rapid global spread of the COVID-19 and many countries have announced the temporary closure of schools, which affects more than 91 percent of the world's students - 1.6 billion children and youth[2]. In this case, we hope that CAT educational version will enable students to learn about cutting-edge knowledge, stimulate students' interest so that students will further learn related knowledge through the Internet. Thus, students can build a foundation for higher level learning through CAT educational version.
For teachers, CAT educational version can be a platform for teaching biology or computer courses related to practical applications, enriching the form and content of the classroom and improving the quality of online education. We welcome teachers to use CAT educational version in the class to guide students with a practical example.
Goal 9: Industries, Innovation and Infrastructure
Inclusive and sustainable industrialization, innovation and infrastructure, can make the economy more dynamic and generate employment and income. In addition, they play a key role in introducing and promoting new technologies, facilitating international trade and enabling the efficient use of resources.
Global manufacturing growth had been gradually declining even before the epidemic, while the COVID-19 dealt a severe blow to manufacturing, disrupting global chains and product supply. Innovation and technological progress are key to finding lasting solutions to economic and environmental challenges, such as increased resource and energy efficiency, and therefore greater investment in research and innovation is required to accelerate manufacturing growth in the current circumstances.
We note that almost the entire population of the world lives in areas covered by mobile networks. It is estimated that in 2019, 96.5% are covered by at least a 2G network with 81.8% covered by at least a Long-Term Evolution network[3]. So the enrichment of knowledge in the Internet and the production of more online tools can ensure people around the world work entrepreneurially and innovatively, which offset the impact of the epidemic and the gap between different levels of development.
CAT was designed to build an online toolset for researchers in protein-related fields to make protein property predictions easily and quickly. By using CAT, users can use machine learning methods to make protein predictions and obtain relevant reference data. With the development of machine learning for protein prediction, CAT will introduce more and more accurate online prediction tools in the foreseeable future, becoming an online platform that integrates most of the mainstream machine learning methods for protein property prediction. Furthermore, we hope that CAT can become an open platform for researchers to submit models with a standardized form and share achievement, which will definitely make CAT become stronger and bigger.
We believe that with the help of CAT, more researchers can participate in protein prediction, promote protein engineering, and provide more effective solutions for agriculture, medicine, environment, etc. We hope that with the continuous development and progress of bioinformatics, machine learning can be better involved in biological research.
Reference
Contact Us
Mail:
USTC_Software2021@163.com
University of Science and Technology of China, No.96, JinZhai Road Baohe District, Hefei, Anhui, 230026, P.R.China
