Hi there! I'm a PhD student at the School of Life Science and Technology, Huazhong University of Science & Technology. My research focuses on leveraging AI tools to address challenges in the microbiome field. I'm passionate about combining computational methods with biological data to uncover new insights and advance our understanding of microbial communities.
- π¦ Microbiome Analysis: Exploring the diversity and functionality of microbial communities in various environments.
- π€ Artificial Intelligence: Applying machine learning and deep learning techniques to analyze and interpret complex biological data.
- π» Bioinformatics: Developing and utilizing computational tools to process and analyze genomic and metagenomic data.
- π¬ Data Integration: Combining multi-omics data to gain a comprehensive understanding of microbiome dynamics.
MGM (Microbial General Model) is a large-scale pretrained language model designed for interpretable microbiome data analysis. MGM allows for fine-tuning and evaluation across various microbiome data analysis tasks.
ASD-cancer (autoencoder-based subtypes detector for cancer) is a semi-supervised deep learning framework based on autoencoder to identify cancer survival subtypes by integrating tumor microbiome profiles and host gene expression.
DeepMicroCancer is a diagnostic model for cancer diagnosis using transfer learning techniques for various cancer types. The model is built using a combination of Random Forest and Transfer Learning techniques.
- π§ Email: [email protected]
- πΌ LinkedIn: Haohong Zhang
- π¦ Twitter: @ludens_zhang
Feel free to explore my repositories, which include scripts, datasets, and tools related to my research. If you find my work interesting or useful, I would love to hear from you. Contributions, issues, and pull requests are welcome!
This README is a reflection of my journey and passion in the field of microbiome research. Stay tuned for more updates and exciting projects! π