Research Areas研究方向
Focusing on crop genomics, computational biology, and plant molecular mechanisms 聚焦作物基因组学、计算生物学及植物分子机制
1. Crop Genomics Decoding1. 作物基因组学破译
Structural Variations and Evolutionary Patterns植物基因组结构与演化规律
Focusing on important economic crops such as cotton and soybean, we utilize cutting-edge sequencing technologies and bioinformatics approaches to decode the fine structure and evolutionary history of complex plant genomes.
By deciphering the genomes of over 31 crops, we have revealed the mechanisms of gene expression rewiring during polyploidization, laying a crucial genomic foundation for molecular design breeding.
本研究方向聚焦于棉花、大豆等重要经济作物。利用最新的三代测序技术和生物信息学手段，我们致力于解析复杂植物基因组的精细结构与演化规律。
通过联合破译31个经济作物的基因组，我们揭示了多倍化过程中基因表达的重塑机制，为作物的分子设计育种提供了重要的基因组学基础。
2. Software & Database Development2. 计算生物学软件及数据库开发
Multi-omics Integration Platforms多组学整合分析平台
With the explosive growth of multi-omics data (genomics, transcriptomics, epigenomics, and metabolomics), developing highly efficient algorithms and tools has become a critical bottleneck in biological research.
Our team has independently developed multiple pipelines and software for multi-omics integration, establishing public databases that significantly promote global data sharing and mining.
随着多组学（基因组、转录组、表观组、代谢组）数据的爆炸式增长，开发高效的算法和工具成为生物学研究的瓶颈。
团队自主开发了多套多组学整合分析流程和软件，搭建了面向公众的综合性组学数据库平台。这极大推动了组学数据在全球范围内的共享与挖掘。
3. Functional Genes & Metabolic Regulation3. 植物功能基因及其代谢调控机制
Dry & Wet Lab Combination生物信息预测与干湿实验结合
Based on bioinformatics predictions, this direction combines molecular biology experiments ("dry and wet lab") to deeply explore key functional genes involved in plant development and stress responses.
By mapping regulatory networks between genes and metabolites, we elucidate the molecular mechanisms behind important agronomic traits, providing direct targets for precision crop improvement.
在生物信息学预测的基础上，本方向结合分子生物学“干湿结合”的实验验证，深入探讨植物发育及抗逆境过程中的关键功能基因。
通过挖掘功能基因及其代谢物调控网络，阐明植物重要农艺性状形成的分子机理，为实现作物的精准改良与抗性提升提供直接的靶点。