Protein engineering has made significant contributions to industries such as agriculture, food, and pharmaceuticals. In recent years, directed evolution combined with artificial intelligence has emerged as a cutting-edge R&D approach. However, the application of machine learning techniques can be challenging for those without relevant experience and coding skills. To address this issue, we have developed a web-based protein sequence recommendation system: STAR (Sequence recommendaTion via ARtificial intelligence). Our system utilizes Bayesian optimization as its backbone and includes a filtering step using a regression model to enhance the success rate of recommended sequences. Additionally, we have incorporated an in silico-directed evolution approach to expand the exploration of the protein space. The Web site can be accessed at https://www.FindProteinStar.com/.
STAR: A Web Server for Assisting Directed Protein Evolution with Machine Learning.
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作者:Yang Likun, Liang Xiaoli, Zhang Na, Lu Lu
| 期刊: | ACS Omega | 影响因子: | 4.300 |
| 时间: | 2023 | 起止号: | 2023 Nov 14; 8(47):44751-44756 |
| doi: | 10.1021/acsomega.3c04832 | ||
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