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2025年10月，课题组长段斌受邀参加2025年第四届全国系统生物学大会并发表主题为Linking Spatial Transcriptomics to Clinical Phenotypes with Interpretable Machine Learning的演讲。

In conclusion, we conducted a comprehensive examination of the morphological features and heterogeneity of CTCs across a variety of cancer types, with a primary focus on HCC due to its predominance in our dataset. The ML-based model for CTC recognition developed here could significantly enhance the accuracy and feasibility of CTC analysis in the clinical setting.

2025年4月，课题组长段斌受邀参加第四届中国智能健康与生物信息大会。

2025年3月，课题组长段斌当选上海市药学会首届人工智能药学专业委员会青年委员会委员。

2025年2月22日（星期六），课题组长段斌在上海交通大学系统生物医学教育部重点实验室2024年度学术委员会会议上做代表性学术报告（报告主题：《基于细胞类型空间邻域嵌入的多切片空间域综合分析系统SpaDo》）。

2024年11月27日（星期三），课题组长段斌在上海交通大学系统生物医学研究院发表“人工智能驱动的肿瘤微环境下基因型-表型解析研究”主题演讲。

2024年10月28日（星期一），课题组长段斌在同济大学发表“整合空间转录组多切片的空间域综合分析系统SpaDo”主题演讲。

In summary, PerturBase stands as a pioneering, high-content database intended for searching, visualizing and analyzing scPerturbation datasets, contributing to a deeper understanding of perturbation effects.

Here, we comprehensively summarize recent advances in single-cell omics technologies, with a specific focus on the methodology section. This overview aims to guide researchers in selecting appropriate methods for single-cell sequencing and related data analysis.

We demonstrate SpaDo’s effectiveness with over 40 multi-slice spatial transcriptome datasets from 7 sequencing platforms. Our findings highlight SpaDo’s potential to reveal novel biological insights in multi-slice spatial transcriptomes.