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| title: README | |
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| # 🧬 Xu Lab | |
| ### AI for Protein Engineering, Bioinformatics, and Scientific Discovery | |
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| ## About Us | |
| **Xu Lab** is a research group working at the intersection of **artificial intelligence**, **bioinformatics**, **computational biology**, and **protein engineering**. We develop practical, interpretable, and reproducible machine-learning methods for understanding and engineering biological sequences and structures. | |
| Our work aims to improve mutation-effect prediction, accelerate AI-assisted directed evolution, and build open research resources that support biological design and discovery. | |
| ## Research Areas | |
| - **Protein mutation-effect prediction** — predicting the effects of amino-acid substitutions on protein stability, pH-related properties, solubility, and other functional traits. | |
| - **AI-assisted protein engineering and directed evolution** — prioritizing beneficial mutations and multi-site variants to improve experimental screening efficiency. | |
| - **Codon language models and codon optimization** — learning codon-level representations and designing coding sequences with improved expression and host compatibility. | |
| - **Protein sequence–structure learning** — integrating protein language models, structural priors, graph representations, and multimodal neural networks. | |
| - **Biosynthetic gene cluster discovery** — identifying BGC boundaries, classes, core biosynthetic enzymes, and distant homologs from complete genomes and metagenomic contigs. | |
| - **Reinforcement learning for biological sequence optimization** — optimizing protein and nucleotide sequences under multiple biological objectives and constraints. | |
| - **Open and reproducible bioinformatics** — developing datasets, benchmarks, data-cleaning pipelines, models, and software for transparent scientific research. | |
| ## Collaboration and Recruitment | |
| We welcome collaboration with researchers and organizations working in machine learning, bioinformatics, protein engineering, synthetic biology, and computational biology. | |
| Xu Lab is also interested in recruiting motivated undergraduate and graduate students with backgrounds in **data analysis**, **machine learning**, **deep learning**, **bioinformatics**, or **protein bioengineering**. | |
| ## Contact | |
| - **Email:** [xyx@zuel.edu.cn](mailto:xyx@zuel.edu.cn) | |
| - **Homepage:** [Xu Lab Homepage](https://xulab-research.yuque.com/r/organizations/homepage) | |
| - **GitHub:** [xulab-research](https://github.com/xulab-research) | |
| - **ORCID:** [0000-0002-9981-2097](https://orcid.org/0000-0002-9981-2097) | |
| - **Google Scholar:** [Academic Profile](https://scholar.google.com/citations?user=PpO2_vsAAAAJ) | |
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| <strong>Xu Lab · Exploring biology with AI</strong> 🌱 | |
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