Researchers from Zhejiang University and HKUST (Guangzhou) have developed a cutting-edge AI model, ProtET, that leverages multi-modal learning to enable controllable protein editing through text-based instructions. This innovative approach, published in Health Data Science, bridges the gap between biological language and protein sequence manipulation, enhancing functional protein design across domains like enzyme activity, stability, and antibody binding.
Proteins are the cornerstone of biological functions, and their precise modification holds immense potential for medical therapies, synthetic biology, and biotechnology. While traditional protein editing methods rely on labor-intensive laboratory experiments and single-task optimization models, ProtET introduces a transformer-structured encoder architecture and a hierarchical training paradigm. This model aligns protein sequences with natural language descriptions using contrastive learning, enabling intuitive, text-guided protein modifications.
The research team, led by Mingze Yin from Zhejiang University and Jintai Chen from HKUST (Guangzhou), trained ProtET on a dataset of over 67 million protein–biotext pairs, extracted from Swiss-Prot and TrEMBL databases. The model demonstrated exceptional performance across key benchmarks, improving protein stability by up to 16.9% and optimizing catalytic activities and antibody-specific binding.
A breakthrough by Chinese researchers could help solve complex problems in industries ranging from aerospace to bridge design.
We often see stories of invincible warriors with superhuman abilities combating monstrous threats, but are the days of super soldiers nearly upon us, and could they be the biggest threat of all?
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/ discord Credits: Super Soldiers Science & Futurism with Isaac Arthur Episode 381a, February 12, 2023 Written, Produced & Narrated by Isaac Arthur Editors: Briana Brownell David McFarlane Lukas Konecny Music Courtesy of Epidemic Sound http://epidemicsound.com/creator.
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Credits:
Super Soldiers.
Science & Futurism with Isaac Arthur.
Episode 381a, February 12, 2023
Written, Produced & Narrated by Isaac Arthur.
Editors:
The particle-physics funder will provide financial incentives to encourage practices such as data sharing and transparent peer review.
When I saw the introduction of this game, the word “edutainment” popped up in my mind. It definitely turns coding into a more fun, satisfying activity.
“Use real Python code to automate machines, robots, drones and more: Program self-driving vehicles; crack passwords; apply machine learning; automate logistics; use image processing to guide missiles,” the description of JOY OF PROGRAMMING — Software Engineering Simulator reads.
There are various levels that are ready in the game, whose goals, mandatory or optional ones, can be solved with different valid solutions. When finishing the levels, you’ll gain stars, which are used to unlock new programming features.
OpenAI says no money changed hands in the collaboration. But because the work could benefit Retro—whose biggest investor is Altman—the announcement may add to questions swirling around the OpenAI CEO’s side projects.
Last year, the Wall Street Journal said Altman’s wide-ranging investments in private tech startups amount to an “opaque investment empire” that is “creating a mounting list of potential conflicts,” since some of these companies also do business with OpenAI.
In Retro’s case, simply being associated with Altman, OpenAI, and the race toward AGI could boost its profile and increase its ability to hire staff and raise funds. Betts-Lacroix did not answer questions about whether the early-stage company is currently in fundraising mode.
Researchers have revolutionized quantum technology by achieving long-lasting entanglement between molecules using ‘magic-wavelength optical tweezers.’
This breakthrough enhances the potential for quantum computing.
Performing computation using quantum-mechanical phenomena such as superposition and entanglement.