Awards

NUS iGEM 2023 is proud to have achieved:

Awarded
	Second Runner-Up
	Best Foundational Advance

Nominated for
	Best Composite Part
	Best Model
	Best Wiki
	Best Presentation

Bronze Medal

Name	Description
B1. Competition Deliverables	We have created a comprehensive and well-organized wiki that details our project. We have developed a short and engaging video that introduces our project to you. We have completed our judging form thoroughly and accurately. We have secured a judging session. Presentation video coming soon.
B2. Project Attributions	Check out our Attributions page
B3. Project Description	Check out our Description page
B4. Contribution	GFP-sacB Negative Selection Marker: We created a composite part composed of a green fluorescence reporter protein sequence and a sacB negative selection marker sequence linked by a rigid protein linker. STAR One-Plasmid System: We created a system to efficiently generate single-stranded DNA (ssDNA) using a single-plasmid approach. SIGNAL workflow: We designed the SIGNAL workflow, a High Throughput approach for characterizing RNA switch variation data using unique barcoded oligonucleotides, enabling expanded design space and specificity evaluation for RNA switches. Key steps have been done and developed Large Language Model: We created a pretrained language model, enabling in predicting binding likelihood with a remarkable 0.9 Pearson correlation, featuring a novel Siamese model architecture applicable beyond RNAs. Generative Model: We developed a model capable of generating RNA switches, validated against the Nico et Al toehold dataset, with potential for further optimization through a Reinforcement Learning approach and the generation of mutation data using a proposed wetlab workflow. OTTER interface: We developed the software interface for OTTER to aid RNA switch design process using our models mentioned above. Gene.io Educational Game: We created Gene.io, a synthetic biology game that is available for people to learn what is genetic circuits and how we can construct a genetic circuit correctly. Children's Book: We created a storybook for children to spark their first interest in synthetic biology at a young age.

Silver Medal

Name	Description
S1. Engineering Success	We have demonstrated engineering success in a part of our project by going through at least one iteration of the engineering design cycle (sacB characterisation), which is distinct from our Contribution for Bronze. We have also created a new Part BBa_K4850008 for this criterion and have characterized it as well as clearly document the contribution on that Part's Main Page on the Registry.
S2. Human Practices	We have explained how we have determined our work is responsible and good for the world.

Gold Medal

Name	Description
Best New Composite Part	We have shown that our composite part BBa_K4850008 works as expected experimentally. We have developed an experimental validated ODE model for our composite part BBa_K4850008. The model fits well with the experiment. We have shown how our composite part BBa_K4850008 is useful to the community. We have well characterised (experimentally measured and modeled) our composite part BBa_K4850008.
Model	Our machine learning models helped us understand in-silico RNA-RNA interactions. We have shown how our modeling approach provides a good foundation for others to build upon. We have adapted a generalisable deep learning framework that is good at predicting and generating different RNA switches, and shown that it works.
Education	We encouraged young children to be interested in the field of synthetic biology through a children's book. We have documented our storybook and game in a way that others can build upon. We have shown how the storybook and game was thoughtfully implemented. We have shown how our activites would enable people to shape, contribute to, and/or participate in synthetic biology.